subject:(Multi Objective Optimization)

University of Cambridge

1. Lattarulo, Valerio. Development of a Multi-objective Variant of the Alliance Algorithm.

Degree: PhD, 2017, University of Cambridge

URL: https://www.repository.cam.ac.uk/handle/1810/270076

► Optimization methodologies are particularly relevant nowadays due to the ever-increasing power of computers and the enhancement of mathematical models to better capture reality. These computational… (more)

▼ Optimization methodologies are particularly relevant nowadays due to the ever-increasing power of computers and the enhancement of mathematical models to better capture reality. These computational methods are used in many different fields and some of them, such as metaheuristics, have often been found helpful and efficient for the resolution of practical applications where finding optimal solutions is not straightforward. Many practical applications are multi-objective optimization problems: there is more than one objective to optimize and the solutions found represent trade-offs between the competing objectives. In the last couple of decades, several metaheuristics approaches have been developed and applied to practical problems and multi-objective versions of the main single-objective approaches were created. The Alliance Algorithm (AA) is a recently developed single-objective optimization algorithm based on the metaphorical idea that several tribes, with certain skills and resource needs, try to conquer an environment for their survival and try to ally together to improve the likelihood of conquest. The AA method has yielded reasonable results in several fields to which it has been applied, thus the development in this thesis of a multi-objective variant to handle a wider range of problems is a natural extension. The first challenge in the development of the Multi-objective Alliance Algorithm (MOAA) was acquiring an understanding of the modifications needed for this generalization. The initial version was followed by other versions with the aim of improving MOAA performance to enable its use in solving real-world problems: the most relevant variations, which led to the final version of the approach, have been presented. The second major contribution in this research was the development and combination of features or the appropriate modification of methodologies from the literature to fit within the MOAA and enhance its potential and performance. An analysis of the features in the final version of the algorithm was performed to better understand and verify their behavior and relevance within the algorithm. The third contribution was the testing of the algorithm on a test-bed of problems. The results were compared with those obtained using well-known baseline algorithms. Moreover, the last version of the MOAA was also applied to a number of real-world problems and the results, compared against those given by baseline approaches, are discussed. Overall, the results have shown that the MOAA is a competitive approach which can be used `out-of-the-box' on problems with different mathematical characteristics and in a wide range of applications. Finally, a summary of the objectives achieved, the current status of the research and the work that can be done in future to further improve the performance of the algorithm is provided.

Subjects/Keywords: optimization; multi-objective; algorithm

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APA (6^th Edition):

Lattarulo, V. (2017). Development of a Multi-objective Variant of the Alliance Algorithm. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/270076

Chicago Manual of Style (16^th Edition):

Lattarulo, Valerio. “Development of a Multi-objective Variant of the Alliance Algorithm.” 2017. Doctoral Dissertation, University of Cambridge. Accessed January 27, 2021. https://www.repository.cam.ac.uk/handle/1810/270076.

MLA Handbook (7^th Edition):

Lattarulo, Valerio. “Development of a Multi-objective Variant of the Alliance Algorithm.” 2017. Web. 27 Jan 2021.

Vancouver:

Lattarulo V. Development of a Multi-objective Variant of the Alliance Algorithm. [Internet] [Doctoral dissertation]. University of Cambridge; 2017. [cited 2021 Jan 27]. Available from: https://www.repository.cam.ac.uk/handle/1810/270076.

Council of Science Editors:

Lattarulo V. Development of a Multi-objective Variant of the Alliance Algorithm. [Doctoral Dissertation]. University of Cambridge; 2017. Available from: https://www.repository.cam.ac.uk/handle/1810/270076

University of New South Wales

2. Zhang, Bin. Online Knowledge-based Evolutionary Multi-objective Optimisation.

Degree: Engineering & Information Technology, 2015, University of New South Wales

URL: http://handle.unsw.edu.au/1959.4/55251 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36875/SOURCE02?view=true

► Knowledge-based optimization is a recent direction in evolutionary optimization research which aims at understanding the optimization process, discovering relationships between decision variables and performance parameters,… (more)

Subjects/Keywords: Knowledge-based Multi-objective Evolutionary Optimization; Evolutionary Multi-objective Optimization; Evolutionary Many-objective Optimization

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APA (6^th Edition):

Zhang, B. (2015). Online Knowledge-based Evolutionary Multi-objective Optimisation. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/55251 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36875/SOURCE02?view=true

Chicago Manual of Style (16^th Edition):

Zhang, Bin. “Online Knowledge-based Evolutionary Multi-objective Optimisation.” 2015. Doctoral Dissertation, University of New South Wales. Accessed January 27, 2021. http://handle.unsw.edu.au/1959.4/55251 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36875/SOURCE02?view=true.

MLA Handbook (7^th Edition):

Zhang, Bin. “Online Knowledge-based Evolutionary Multi-objective Optimisation.” 2015. Web. 27 Jan 2021.

Vancouver:

Zhang B. Online Knowledge-based Evolutionary Multi-objective Optimisation. [Internet] [Doctoral dissertation]. University of New South Wales; 2015. [cited 2021 Jan 27]. Available from: http://handle.unsw.edu.au/1959.4/55251 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36875/SOURCE02?view=true.

Council of Science Editors:

Zhang B. Online Knowledge-based Evolutionary Multi-objective Optimisation. [Doctoral Dissertation]. University of New South Wales; 2015. Available from: http://handle.unsw.edu.au/1959.4/55251 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36875/SOURCE02?view=true

Texas A&M University

3. McDonald, Walter. A Multi-Objective Ant Colony Optimization Algorithm for Infrastructure Routing.

Degree: MS, Civil Engineering, 2012, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11093

► An algorithm is presented that is capable of producing Pareto-optimal solutions for multi-objective infrastructure routing problems: the Multi-Objective Ant Colony Optimization (MOACO). This algorithm offers… (more)

Subjects/Keywords: Ant Colony Optimization; Multi-Objective; Multi-Objective Ant Colony Optimization

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APA (6^th Edition):

McDonald, W. (2012). A Multi-Objective Ant Colony Optimization Algorithm for Infrastructure Routing. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11093

Chicago Manual of Style (16^th Edition):

McDonald, Walter. “A Multi-Objective Ant Colony Optimization Algorithm for Infrastructure Routing.” 2012. Masters Thesis, Texas A&M University. Accessed January 27, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11093.

MLA Handbook (7^th Edition):

McDonald, Walter. “A Multi-Objective Ant Colony Optimization Algorithm for Infrastructure Routing.” 2012. Web. 27 Jan 2021.

Vancouver:

McDonald W. A Multi-Objective Ant Colony Optimization Algorithm for Infrastructure Routing. [Internet] [Masters thesis]. Texas A&M University; 2012. [cited 2021 Jan 27]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11093.

Council of Science Editors:

McDonald W. A Multi-Objective Ant Colony Optimization Algorithm for Infrastructure Routing. [Masters Thesis]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11093

Universitat Politècnica de València

4. Siurana Paula, Maria. Modelling and multiobjective optimization for simulation of cyanobacterial metabolism .

Degree: 2017, Universitat Politècnica de València

URL: http://hdl.handle.net/10251/90578

► The present thesis is devoted to the development of models and algorithms to improve metabolic simulations of cyanobacterial metabolism. Cyanobacteria are photosynthetic bacteria of great… (more)

▼ The present thesis is devoted to the development of models and algorithms to improve metabolic simulations of cyanobacterial metabolism. Cyanobacteria are photosynthetic bacteria of great biotechnological interest to the development of sustainable bio-based manufacturing processes. For this purpose, it is fundamental to understand metabolic behaviour of these organisms, and constraint-based metabolic modelling techniques offer a platform for analysis and assessment of cell's metabolic functionality. Reliable simulations are needed to enhance the applicability of the results, and this is the main goal of this thesis. This dissertation has been structured in three parts. The first part is devoted to introduce needed fundamentals of the disciplines that are combined in this work: metabolic modelling, cyanobacterial metabolism and multi-objective optimisation. In the second part the reconstruction and update of metabolic models of two cyanobacterial strains is addressed. These models are then used to perform metabolic simulations with the application of the classic Flux Balance Analysis (FBA) methodology. The studies conducted in this part are useful to illustrate the uses and applications of metabolic simulations for the analysis of living organisms. And at the same time they serve to identify important limitations of classic simulation techniques based on mono-objective linear optimisation that motivate the search of new strategies. Finally, in the third part a novel approach is defined based on the application of multi-objective optimisation procedures to metabolic modelling. Main steps in the definition of multi-objective problem and the description of an optimisation algorithm that ensure the applicability of the obtained results, as well as the multi-criteria analysis of the solutions are covered. The resulting tool allows the definition of non-linear objective functions and constraints, as well as the analysis of multiple Pareto-optimal solutions. It avoids some of the main drawbacks of classic methodologies, leading to more flexible simulations and more realistic results. Overall this thesis contributes to the advance in the study of cyanobacterial metabolism by means of definition of models and strategies that improve plasticity and predictive capacities of metabolic simulations.; La presente tesis está dedicada al desarrollo de modelos y algoritmos para mejorar las simulaciones metabólicas de cianobacterias. Las cianobacterias son bacterias fotosintéticas de gran interés biotecnológico para el desarrollo de bioprocesos productivos sostenibles. Para este propósito, es fundamental entender el comportamiento metabólico de estos organismos, y el modelado metabólico basado en restricciones ofrece una plataforma para el análisis y la evaluación de las funcionalidades metabólicas de las células. Se necesitan simulaciones fidedignas para aumentar la aplicabilidad de los resultados, y este es el objetivo principal de esta tesis. Esta disertación se ha estructurado en tres partes. La primera parte está dedicada a… Advisors/Committee Members: Fernández de Córdoba Castellá, Pedro José (advisor), Montagud Aquino, Arnau (advisor), Reynoso Meza, Gilberto (advisor).

Subjects/Keywords: metabolic modelling; metabolic modeling; cyanobacteria; multi-objective optimisation; multi-objective optimization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Siurana Paula, M. (2017). Modelling and multiobjective optimization for simulation of cyanobacterial metabolism . (Doctoral Dissertation). Universitat Politècnica de València. Retrieved from http://hdl.handle.net/10251/90578

Chicago Manual of Style (16^th Edition):

Siurana Paula, Maria. “Modelling and multiobjective optimization for simulation of cyanobacterial metabolism .” 2017. Doctoral Dissertation, Universitat Politècnica de València. Accessed January 27, 2021. http://hdl.handle.net/10251/90578.

MLA Handbook (7^th Edition):

Siurana Paula, Maria. “Modelling and multiobjective optimization for simulation of cyanobacterial metabolism .” 2017. Web. 27 Jan 2021.

Vancouver:

Siurana Paula M. Modelling and multiobjective optimization for simulation of cyanobacterial metabolism . [Internet] [Doctoral dissertation]. Universitat Politècnica de València; 2017. [cited 2021 Jan 27]. Available from: http://hdl.handle.net/10251/90578.

Council of Science Editors:

Siurana Paula M. Modelling and multiobjective optimization for simulation of cyanobacterial metabolism . [Doctoral Dissertation]. Universitat Politècnica de València; 2017. Available from: http://hdl.handle.net/10251/90578

Anna University

5. Ganesan H. A study on multi objective optimization of process parameters in turning process using evolutionary algorithms;.

Degree: process parameters in turning process using evolutionary algorithms, 2014, Anna University

URL: http://shodhganga.inflibnet.ac.in/handle/10603/26237

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Economy of machinery operation plays a key role in competitiveness in newlinethe market In a manufacturing industry machining process is to shape the newlinemetal parts… (more)

Subjects/Keywords: evolutionary algorithms; mechanical engineering; multi objective optimization

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APA (6^th Edition):

H, G. (2014). A study on multi objective optimization of process parameters in turning process using evolutionary algorithms;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/26237

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

H, Ganesan. “A study on multi objective optimization of process parameters in turning process using evolutionary algorithms;.” 2014. Thesis, Anna University. Accessed January 27, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/26237.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

H, Ganesan. “A study on multi objective optimization of process parameters in turning process using evolutionary algorithms;.” 2014. Web. 27 Jan 2021.

Vancouver:

H G. A study on multi objective optimization of process parameters in turning process using evolutionary algorithms;. [Internet] [Thesis]. Anna University; 2014. [cited 2021 Jan 27]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/26237.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

H G. A study on multi objective optimization of process parameters in turning process using evolutionary algorithms;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/26237

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

6. Li, Kaiming. Broadband lossy impedance matching of antennas.

Degree: 2016, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/28029

► In RF applications such as transmitters, amplifiers, receivers, and antennas, a task of vital importance is the design of an impedance matching network, one that… (more)

▼ In RF applications such as transmitters, amplifiers, receivers, and antennas, a task of vital importance is the design of an impedance matching network, one that can transfer the most power from the source to the load. Lossless matching networks at a single frequency have been well studied, while the broadband impedance matching problem was only defined 70 years ago. This dissertation provides a thorough background of the theory basis and design approaches in the history of broadband impedance matching. Lossless impedance matching optimization using the MATLAB Global Optimization Toolbox is discussed, and an approach combining brute-force techniques and the Real Frequency Technique is proposed. The bandwidth of a candidate 80-meter high-frequency dipole antenna has been increased from 4.1% to at least 15.0% after the optimization, with a Voltage Standing Wave Ratio (VSWR) of 2:1. In order to match the source and load over a wide band, a tradeoff is forced between the antenna gain and its bandwidth. The lossy impedance matching problem is investigated in the dissertation as a multi-objective optimization problem. Multiple optimization algorithms are used to find the Pareto front for a given lossy network topology. With equal weight on the objectives, the bandwidth of the dipole is further increased to 16.9%. This approach was applied to conformal antennas such as a low-profile bow-tie antenna close to a ground plane and compared with the new approach of using metamaterial inserted between the antenna and the ground plane. There is considerable interest and a main goal of this dissertation to find if another approach such as this lossy matching method could compete with the metamaterial technique. With lossy matching, the unnecessarily high gain of the antenna is traded in for a decrease in the reflection, increasing the bandwidth of the bow-tie to more than 70.7%, or [200MHz, 400MHz]. Considering the high cost of manufacturing metamaterial to achieve similar performance, the approach found for the first time in this dissertation is a iv significant breakthrough in the design and practicality of making future conformal and other types of antennas. The unique and innovative techniques utilized in this dissertation include performing lossless and lossy impedance matching optimization using results from more numerical platforms like FEKO and GNEC for various antenna configurations. In this dissertation topologies have been thoroughly explored including circuits with various numbers of elements and those including the insertion of lossy components into the lossless networks. Additionally, the latest nature-inspired optimization algorithms were applied to the lossy impedance matching problem and compared with the traditional algorithms. Advisors/Committee Members: James Kenneth Breakall, Dissertation Advisor/Co-Advisor, James Kenneth Breakall, Committee Chair/Co-Chair, Ram Mohan Narayanan, Committee Member, Shizhuo Yin, Committee Member, Michael T Lanagan, Committee Member.

Subjects/Keywords: Broadband antennas; impedance matching; multi-objective optimization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Li, K. (2016). Broadband lossy impedance matching of antennas. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/28029

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Li, Kaiming. “Broadband lossy impedance matching of antennas.” 2016. Thesis, Penn State University. Accessed January 27, 2021. https://submit-etda.libraries.psu.edu/catalog/28029.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Li, Kaiming. “Broadband lossy impedance matching of antennas.” 2016. Web. 27 Jan 2021.

Vancouver:

Li K. Broadband lossy impedance matching of antennas. [Internet] [Thesis]. Penn State University; 2016. [cited 2021 Jan 27]. Available from: https://submit-etda.libraries.psu.edu/catalog/28029.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Li K. Broadband lossy impedance matching of antennas. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/28029

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Newcastle

7. Mortazavi Naeini, Seyed Mohammad. Multi-objective optimization of urban water resource systems.

Degree: PhD, 2013, University of Newcastle

URL: http://hdl.handle.net/1959.13/938722

►

Research Doctorate - Doctor of Philosophy (PhD)

The provision of a water supply that is secure in the face of severe drought is a primary… (more)

▼

Research Doctorate - Doctor of Philosophy (PhD)

The provision of a water supply that is secure in the face of severe drought is a primary objective for urban water agencies – “running out of water” is not a viable option for a large city. However, there are other objectives that conflict with the primary one – these include minimizing costs and environmental impacts. A major challenge facing decision makers in the urban water sector is dealing with the trade-offs between these conflicting objectives. Multi-objective optimization methods have the potential to identify the optimal trade-offs between the competing objectives. The principal aim of this thesis is to address the shortcomings in existing multi-objective optimization applications to produce methods of greater practical relevance to urban water resource management. Review of past studies identified three practically significant shortcomings. Focusing exclusively on either long-term (or infrastructure) options or on short-term options such as operation rules may lead to sub-optimal solutions. The use of short climate forcing data time series in simulation models to evaluate drought security can produce solutions that make the system highly vulnerable to severe drought. Finally, the setting of a priori environmental constraints may hide trade-offs between environmental, economic and security factors that are of considerable interest to decision makers. These shortcomings are addressed by a new multi-objective methodology that exploits the ability of evolutionary algorithms to handle complex objective functions and simulation models. The principal novelty is the explicit treatment of drought security. A case study based on the headworks system for Australia’s largest city, Sydney, demonstrates the practical significance of these shortcomings and, importantly, the ability of the new approach to deal with these shortcomings in a practicable manner. In the face of urban population growth and the accompanying growth in water demand, the performance of the urban water resource system is expected to deteriorate over time. This will result in the need to intervene and adapt the system to the changing conditions. The scheduling capacity expansion problem seeks to identify the optimal schedule for the changes to the system. In past studies, this problem has been largely tackled by minimizing the total present worth of capital, operational and rationing costs. A significant drawback of minimizing the total present worth cost is that it is likely to produce solutions that lead to more severe and frequent rationing in the future. Such a solution is likely to be socially unacceptable. A multi-objective formulation for the scheduling capacity expansion problem is developed to overcome this shortcoming while addressing the need to explicitly deal with drought security and jointly optimize operating and infrastructure decisions. The formulation enables the trade-off between cost and equity (the equal sharing of the burden of restrictions over the planning horizon) to be…

Advisors/Committee Members: University of Newcastle. Faculty of Engineering and Built Environment, School of Engineering.

Subjects/Keywords: multi-objective; optimization; scheduling; urban water management

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APA (6^th Edition):

Mortazavi Naeini, S. M. (2013). Multi-objective optimization of urban water resource systems. (Doctoral Dissertation). University of Newcastle. Retrieved from http://hdl.handle.net/1959.13/938722

Chicago Manual of Style (16^th Edition):

Mortazavi Naeini, Seyed Mohammad. “Multi-objective optimization of urban water resource systems.” 2013. Doctoral Dissertation, University of Newcastle. Accessed January 27, 2021. http://hdl.handle.net/1959.13/938722.

MLA Handbook (7^th Edition):

Mortazavi Naeini, Seyed Mohammad. “Multi-objective optimization of urban water resource systems.” 2013. Web. 27 Jan 2021.

Vancouver:

Mortazavi Naeini SM. Multi-objective optimization of urban water resource systems. [Internet] [Doctoral dissertation]. University of Newcastle; 2013. [cited 2021 Jan 27]. Available from: http://hdl.handle.net/1959.13/938722.

Council of Science Editors:

Mortazavi Naeini SM. Multi-objective optimization of urban water resource systems. [Doctoral Dissertation]. University of Newcastle; 2013. Available from: http://hdl.handle.net/1959.13/938722

Syracuse University

8. Gunasekara, R Chulaka. Identification of key players in networks using multi-objective optimization and its applications.

Degree: PhD, Electrical Engineering and Computer Science, 2016, Syracuse University

URL: https://surface.syr.edu/etd/579

► Identification of a set of key players, is of interest in many disciplines such as sociology, politics, finance, economics, etc. Although many algorithms have… (more)

▼ Identification of a set of key players, is of interest in many disciplines such as sociology, politics, finance, economics, etc. Although many algorithms have been proposed to identify a set of key players, each emphasizes a single objective of interest. Consequently, the prevailing deficiency of each of these methods is that, they perform well only when we consider their objective of interest as the only characteristic that the set of key players should have. But in complicated real life applications, we need a set of key players which can perform well with respect to multiple objectives of interest. In this dissertation, a new perspective for key player identification is proposed, based on optimizing multiple objectives of interest. The proposed approach is useful in identifying both key nodes and key edges in networks. Experimental results show that the sets of key players which optimize multiple objectives perform better than the key players identified using existing algorithms, in multiple applications such as eventual influence limitation problem, immunization problem, improving the fault tolerance of the smart grid, etc. We utilize multi-objective optimization algorithms to optimize a set of objectives for a particular application. A large number of solutions are obtained when the number of objectives is high and the objectives are uncorrelated. But decision-makers usually require one or two solutions for their applications. In addition, the computational time required for multi-objective optimization increases with the number of objectives. A novel approach to obtain a subset of the Pareto optimal solutions is proposed and shown to alleviate the aforementioned problems. As the size and the complexity of the networks increase, so does the computational effort needed to compute the network analysis measures. We show that degree centrality based network sampling can be used to reduce the running times without compromising the quality of key nodes obtained. Advisors/Committee Members: Kishan G. Mehrotra, Chilukuri K. Mohan.

Subjects/Keywords: Key Players; Multi-objective optimization; Networks; Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Gunasekara, R. C. (2016). Identification of key players in networks using multi-objective optimization and its applications. (Doctoral Dissertation). Syracuse University. Retrieved from https://surface.syr.edu/etd/579

Chicago Manual of Style (16^th Edition):

Gunasekara, R Chulaka. “Identification of key players in networks using multi-objective optimization and its applications.” 2016. Doctoral Dissertation, Syracuse University. Accessed January 27, 2021. https://surface.syr.edu/etd/579.

MLA Handbook (7^th Edition):

Gunasekara, R Chulaka. “Identification of key players in networks using multi-objective optimization and its applications.” 2016. Web. 27 Jan 2021.

Vancouver:

Gunasekara RC. Identification of key players in networks using multi-objective optimization and its applications. [Internet] [Doctoral dissertation]. Syracuse University; 2016. [cited 2021 Jan 27]. Available from: https://surface.syr.edu/etd/579.

Council of Science Editors:

Gunasekara RC. Identification of key players in networks using multi-objective optimization and its applications. [Doctoral Dissertation]. Syracuse University; 2016. Available from: https://surface.syr.edu/etd/579

University of Ontario Institute of Technology

9. Alfughi, Zakiya. Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization.

Degree: 2015, University of Ontario Institute of Technology

URL: http://hdl.handle.net/10155/548

► To acquire the maximum efficiency for solar electricity conversion, a solar panel has to absorb nearly every single photon of light emitted from the sun.… (more)

Subjects/Keywords: Photovoltaic; Parabolic trough panel; Multi-objective optimization

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APA (6^th Edition):

Alfughi, Z. (2015). Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/548

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Alfughi, Zakiya. “Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization.” 2015. Thesis, University of Ontario Institute of Technology. Accessed January 27, 2021. http://hdl.handle.net/10155/548.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Alfughi, Zakiya. “Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization.” 2015. Web. 27 Jan 2021.

Vancouver:

Alfughi Z. Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization. [Internet] [Thesis]. University of Ontario Institute of Technology; 2015. [cited 2021 Jan 27]. Available from: http://hdl.handle.net/10155/548.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Alfughi Z. Optimal farm design with parabolic shape photovoltaic panels using multi-objective optimization. [Thesis]. University of Ontario Institute of Technology; 2015. Available from: http://hdl.handle.net/10155/548

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Virginia Tech

10. Shoghli, Omidreza. A Decison Support System for Multi-Objective Multi-Asset Roadway Asset Management.

Degree: PhD, Civil Engineering, 2014, Virginia Tech

URL: http://hdl.handle.net/10919/64775

► The limited available budget along with old aging infrastructure in nation magnifies the role of strategic decision making for maintenance of infrastructure. The challenging objective… (more)

▼ The limited available budget along with old aging infrastructure in nation magnifies the role of strategic decision making for maintenance of infrastructure. The challenging objective is to maintain the infrastructure asset systems in a state of good repair and to improve the efficiency and performance of the infrastructure systems while protecting and enhancing the natural environment. Decision makers are in need of a decision support system to consider these multiple objectives and criteria to effectively allocate funding and achieve the highest possible return on investment on their infrastructure. The research proposes and validates a framework for such decisions. The proposed model aims at finding optimal techniques for maintenance of multiple roadway asset items while taking into account time, cost, level of service and environmental impacts. Therefore, the goal is to answer what are the optimal combinations of maintenance techniques for roadway assets while more than one objective is being optimized. In other words, the main objective is to develop a decision support system for selecting and prioritizing necessary actions for MRandR (Maintenance, Repair and Rehabilitation) of multiple asset items in order for a roadway to function within an acceptable level of service, budget, and time while considering environmental impacts. To achieve these desirable outcomes, this model creates a two-stage framework for a sustainable infrastructure asset management. First a multi-objective problem based on the multi colony ant colony optimization is analyzed. The objectives of the problem are: (i) Minimizing maintenance costs, (ii) Minimizing maintenance time, (iii) Minimizing environmental impacts and (iv) Maximizing level of service improvement. In the second stage, the results of the multi objective optimization will be prioritized using a Multi Criteria Decision Making (MCDM) process. The proposed approach will simultaneously optimize four conflicting objectives along with using a multi criteria decision-making technique for ranking the resulted non-dominated solutions of multi objective optimization. The results of implementation of the proposed model on a section of I-64 highway are presented for a sub-set of asset items. Moreover, the proposed model is validated using a scalable test problem as well as comparison with existing examples. Results reveal the capability of the model in generation of optimal solutions for the selection of maintenance strategies. The model optimizes decision making process and benefits decision makers by providing them with solutions for infrastructure asset management while meeting national goals towards sustainability and performance-based approach. In addition, provides a tool to run sensitivity analysis to evaluate annual budget effects and environmental impacts of different resource allocation scenarios. Application of the proposed approach is implemented on roadway asset items but it is not limited to roadways and is applicable to other infrastructure assets. Advisors/Committee Members: de la Garza, Jesus M. (committeechair), Sinha, Sunil Kumar (committee member), El-Rayes, Khaled A. (committee member), Garvin, Michael J. (committee member), Wernz, Christian (committee member).

Subjects/Keywords: Roadway Asset Management; Multi-Objective Optimization

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APA (6^th Edition):

Shoghli, O. (2014). A Decison Support System for Multi-Objective Multi-Asset Roadway Asset Management. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64775

Chicago Manual of Style (16^th Edition):

Shoghli, Omidreza. “A Decison Support System for Multi-Objective Multi-Asset Roadway Asset Management.” 2014. Doctoral Dissertation, Virginia Tech. Accessed January 27, 2021. http://hdl.handle.net/10919/64775.

MLA Handbook (7^th Edition):

Shoghli, Omidreza. “A Decison Support System for Multi-Objective Multi-Asset Roadway Asset Management.” 2014. Web. 27 Jan 2021.

Vancouver:

Shoghli O. A Decison Support System for Multi-Objective Multi-Asset Roadway Asset Management. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2021 Jan 27]. Available from: http://hdl.handle.net/10919/64775.

Council of Science Editors:

Shoghli O. A Decison Support System for Multi-Objective Multi-Asset Roadway Asset Management. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/64775

Georgia Tech

11. Herszterg, Ian. Efficient algorithms for solving multi-objective optimization and large-scale transportation problems.

Degree: PhD, Industrial and Systems Engineering, 2020, Georgia Tech

URL: http://hdl.handle.net/1853/63666

► In this thesis, we address two challenges: solving multi-objective integer programs and solving large-scale transportation problems. In Chapter 2, we present a novel fast and… (more)

Subjects/Keywords: Multi-objective optimization; Transportation problems; Heuristics

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APA (6^th Edition):

Herszterg, I. (2020). Efficient algorithms for solving multi-objective optimization and large-scale transportation problems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63666

Chicago Manual of Style (16^th Edition):

Herszterg, Ian. “Efficient algorithms for solving multi-objective optimization and large-scale transportation problems.” 2020. Doctoral Dissertation, Georgia Tech. Accessed January 27, 2021. http://hdl.handle.net/1853/63666.

MLA Handbook (7^th Edition):

Herszterg, Ian. “Efficient algorithms for solving multi-objective optimization and large-scale transportation problems.” 2020. Web. 27 Jan 2021.

Vancouver:

Herszterg I. Efficient algorithms for solving multi-objective optimization and large-scale transportation problems. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Jan 27]. Available from: http://hdl.handle.net/1853/63666.

Council of Science Editors:

Herszterg I. Efficient algorithms for solving multi-objective optimization and large-scale transportation problems. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/63666

University of Akron

12. Kennedy, Marla J. Multi-Objective Optimization of Conventional Surface Water Treatment Processes.

Degree: PhD, Civil Engineering, 2016, University of Akron

URL: http://rave.ohiolink.edu/etdc/view?acc_num=akron1477332989340079

► Optimization of the coagulation/oxidation process in drinking water treatment is essential to ensure that high quality drinking water is provided at minimal cost to the… (more)

▼ Optimization of the coagulation/oxidation process in drinking water treatment is essential to ensure that high quality drinking water is provided at minimal cost to the consumer. While there are many objectives in drinking water treatment, current research in process optimization typically focuses on only one objective. This research focused on the development of an approach for optimizing multiple treatment chemical doses to achieve multiple water quality objectives simultaneously that can be efficiently and effectively implemented for real time process optimization. Neural network process models for the removal of fluorescence components and turbidity were built using operational data collected from Akron Water Supply (AWS) in Akron, Ohio. Model results were generally good, with correlation coefficients for the final models ranging from 0.51 to 0.97.Using these process models, chemical doses were optimized using the Borg genetic algorithm. Results showed that optimization in three dimensions yielded different optimal dosing solutions than optimization in two dimensions, suggesting that optimizing the coagulation process for DOC and cost only would yield suboptimal turbidity removal. Results also showed that many different chemical dosing combinations are capable of meeting specific target water quality values, but their costs varied, suggesting that finding one chemical dosing combination to meet a required turbidity target could be suboptimal in terms of DOC removal and cost. Because genetic algorithms can be time and computationally intensive, an alternative search algorithm was also evaluated for potential online process optimization. Its performance compared with the brute force evaluation of all possible chemical dosing solutions. At dose increments of 1mg/L for four decision variables, the brute force approach required the evaluation of 96,959 potential solutions and required 3.5 minutes to complete the evaluation. In contrast, the search algorithm was able to identify the same optimal solution by evaluating only 376 nodes in 2.2 seconds. Over the 268 days of operational data provided by AWS, the search algorithm was able to identify the same optimal dosing solution for all days, requiring an average of 96% fewer solution evaluations. These results suggest that the search algorithm is ideally suited for automated process control. Advisors/Committee Members: Miller, Christopher (Advisor).

Subjects/Keywords: Engineering; Multi objective optimization, coagulation, fluorescence

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APA (6^th Edition):

Kennedy, M. J. (2016). Multi-Objective Optimization of Conventional Surface Water Treatment Processes. (Doctoral Dissertation). University of Akron. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=akron1477332989340079

Chicago Manual of Style (16^th Edition):

Kennedy, Marla J. “Multi-Objective Optimization of Conventional Surface Water Treatment Processes.” 2016. Doctoral Dissertation, University of Akron. Accessed January 27, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=akron1477332989340079.

MLA Handbook (7^th Edition):

Kennedy, Marla J. “Multi-Objective Optimization of Conventional Surface Water Treatment Processes.” 2016. Web. 27 Jan 2021.

Vancouver:

Kennedy MJ. Multi-Objective Optimization of Conventional Surface Water Treatment Processes. [Internet] [Doctoral dissertation]. University of Akron; 2016. [cited 2021 Jan 27]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1477332989340079.

Council of Science Editors:

Kennedy MJ. Multi-Objective Optimization of Conventional Surface Water Treatment Processes. [Doctoral Dissertation]. University of Akron; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1477332989340079

University of Minnesota

13. Sullivan, Thomas Adam. Multi-domain multi-objective optimization of mechanisms: a general method with two case studies.

Degree: MS, 2013, University of Minnesota

URL: http://hdl.handle.net/11299/162401

► While the design of mechanisms is a well-studied field, current optimization techniques generally focus on the kinematics and dynamics and relegate other aspects of the… (more)

▼ While the design of mechanisms is a well-studied field, current optimization techniques generally focus on the kinematics and dynamics and relegate other aspects of the analysis to separate stages of the overall design process, resulting in a loss of optimality when the entire multi-domain system is considered. This thesis presents a general method by which a mechanism optimization problem may be efficiently formulated and solved, considering multiple competing design objectives across multiple analysis domains. Two case studies illustrate the practical application of this general method. The first is the kinematic-structural optimization of a hydraulic rescue spreader ("jaws of life"). The second is the kinematic-dynamic-thermodynamic optimization of a novel six-bar linkage for an internal combustion engine. A variety of powerful general-purpose multi-objective algorithms are available from the literature. In particular, genetic algorithms are well-suited to multi-objective problems, and the NSGA-II algorithm from this category is employed here. Three strategies are presented to formulate multi-domain mechanism optimizations in a way that can be solved efficiently by a multi-objective genetic algorithm and is free of explicit constraint functions even for complex problems. First, it is shown that the use of non-traditional design variables, such as angles and adaptive interpolations, can result in smaller design spaces to be searched and can guarantee that all optima lie within the selected range of a given design variable. It is also shown that traditional precision-position synthesis techniques can in some cases be employed in a preliminary analysis to reduce the dimension of the design space. Finally, a nested optimization structure is proposed in which kinematic design variables and objectives are optimized in an outer loop, with the non-kinematic problem being optimized in an inner loop at every outer loop iteration, improving the efficiency and stability of the optimization process. These techniques were applied to the hydraulic rescue spreader problem in order to design a six-bar mechanism that could exert a 10,000 pound force through a pair of jaws over a 24 inch spreading distance while maintaining performance-critical kinematic behavior and remaining light and compact enough to be a handheld tool. The structural stresses in each part of the linkage were modeled, using a combination of analytical methods and finite element analysis. The final optimization result was superior to a similar commercially available model with respect to all four kinematic and structural objectives. Having successfully optimized a low-speed mechanism with a structural motivation, the method was also applied to a high-speed mechanism with a thermodynamic motivation. A Stephenson-III six-bar linkage was developed in order to optimize the motion of the piston in an internal combustion engine and achieve a cylinder volume as a function of time most conducive to efficient combustion. A number of mechanical objectives relating to…

Subjects/Keywords: Evolutionary Algorithm; Genetic Algorithm; Mechanisms; Multi-domain; Multi-objective; Optimization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Sullivan, T. A. (2013). Multi-domain multi-objective optimization of mechanisms: a general method with two case studies. (Masters Thesis). University of Minnesota. Retrieved from http://hdl.handle.net/11299/162401

Chicago Manual of Style (16^th Edition):

Sullivan, Thomas Adam. “Multi-domain multi-objective optimization of mechanisms: a general method with two case studies.” 2013. Masters Thesis, University of Minnesota. Accessed January 27, 2021. http://hdl.handle.net/11299/162401.

MLA Handbook (7^th Edition):

Sullivan, Thomas Adam. “Multi-domain multi-objective optimization of mechanisms: a general method with two case studies.” 2013. Web. 27 Jan 2021.

Vancouver:

Sullivan TA. Multi-domain multi-objective optimization of mechanisms: a general method with two case studies. [Internet] [Masters thesis]. University of Minnesota; 2013. [cited 2021 Jan 27]. Available from: http://hdl.handle.net/11299/162401.

Council of Science Editors:

Sullivan TA. Multi-domain multi-objective optimization of mechanisms: a general method with two case studies. [Masters Thesis]. University of Minnesota; 2013. Available from: http://hdl.handle.net/11299/162401

Virginia Tech

14. Young, Alexander Rian. Unified Multi-domain Decision Making: Cognitive Radio and Autonomous Vehicle Convergence.

Degree: PhD, Electrical Engineering, 2013, Virginia Tech

URL: http://hdl.handle.net/10919/19295

► This dissertation presents the theory, design, implementation and successful deployment of a cognitive engine decision algorithm by which a cognitive radio-equipped mobile robot may adapt… (more)

▼ This dissertation presents the theory, design, implementation and successful deployment of a cognitive engine decision algorithm by which a cognitive radio-equipped mobile robot may adapt its motion and radio parameters through multi-objective optimization. This provides a proof-of-concept prototype cognitive system that is aware of its envirionment, its userâ •s needs, and the rules governing its operation. It is to take intelligent action based on this awareness to optimize its performance across both the mobility and radio domains while learning from experience and responding intelligently to ongoing environmental mission changes. The prototype combines the key features of cognitive radios and autonomous vehicles into a single package whose behavior integrates the essential features of both. The use case for this research is a scenario where a small unmanned aerial vehicle (UAV) is traversing a nominally cyclic or repeating flight path (an â •orbitâ •) seeking to observe targets and where possible avoid hostile agents. As the UAV traverses the path, it experiences varying RF effects, including multipath propagation and terrain shadowing. The goal is to provide the capability for the UAV to learn the flight path with respect both to motion and RF characteristics and modify radio parameters and flight characteristics proactively to optimize performance. Using sensor fusion techniques to develop situaitonal awareness, the UAV should be able to adapt its motion or communication based on knolwedge of (but not limited to) physical location, radio performance, and channel conditions. Using sensor information from RF and mobility domains, the UAV uses the mission objectives and its knowledge of the world to decide on a course of action. The UAV develops and executes a multi-domain action; action that crosses domains, such as changing RF power and increasing its speed. This research is based on a simple observation, namely that cognitive radios and autonomous vehicles perform similar tasks, albeit in different domains. Both analyze their environment, make and execute a decision, evaluate the result (learn from experience), and repeat as required. This observation led directly to the creation of a single intelligent agent combining cognitive radio and autonomous vehicle intelligence with the ability to leverage flexibility in the radio frequency (RF) and motion domains. Using a single intelligent agent to optimize decision making across both mobility and radio domains is unified multi-domain decision making (UMDDM). Advisors/Committee Members: Bostian, Charles W. (committeechair), Reed, Jeffrey H. (committee member), Meehan, Kathleen (committee member), Woolsey, Craig A. (committee member), Pratt, Timothy J. (committee member).

Subjects/Keywords: Cognitive Radio; Autonomous Vehicles; Multi-domain Decision Making; Multi-objective Optimization

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APA (6^th Edition):

Young, A. R. (2013). Unified Multi-domain Decision Making: Cognitive Radio and Autonomous Vehicle Convergence. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/19295

Chicago Manual of Style (16^th Edition):

Young, Alexander Rian. “Unified Multi-domain Decision Making: Cognitive Radio and Autonomous Vehicle Convergence.” 2013. Doctoral Dissertation, Virginia Tech. Accessed January 27, 2021. http://hdl.handle.net/10919/19295.

MLA Handbook (7^th Edition):

Young, Alexander Rian. “Unified Multi-domain Decision Making: Cognitive Radio and Autonomous Vehicle Convergence.” 2013. Web. 27 Jan 2021.

Vancouver:

Young AR. Unified Multi-domain Decision Making: Cognitive Radio and Autonomous Vehicle Convergence. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Jan 27]. Available from: http://hdl.handle.net/10919/19295.

Council of Science Editors:

Young AR. Unified Multi-domain Decision Making: Cognitive Radio and Autonomous Vehicle Convergence. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/19295

University of Pretoria

15. Dymond, Antoine Smith Dryden. Multiple objective optimization of an airfoil shape.

Degree: Mechanical and Aeronautical Engineering, 2011, University of Pretoria

URL: http://hdl.handle.net/2263/22939

► An airfoil shape optimization problem with conflicting objectives is handled using two different multi-objective approaches. These are an a priori scalarization approach where the conflicting… (more)

Subjects/Keywords: Real-world optimization; Multi-objective optimization; Undefined regions; UCTD

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APA (6^th Edition):

Dymond, A. S. D. (2011). Multiple objective optimization of an airfoil shape. (Masters Thesis). University of Pretoria. Retrieved from http://hdl.handle.net/2263/22939

Chicago Manual of Style (16^th Edition):

Dymond, Antoine Smith Dryden. “Multiple objective optimization of an airfoil shape.” 2011. Masters Thesis, University of Pretoria. Accessed January 27, 2021. http://hdl.handle.net/2263/22939.

MLA Handbook (7^th Edition):

Dymond, Antoine Smith Dryden. “Multiple objective optimization of an airfoil shape.” 2011. Web. 27 Jan 2021.

Vancouver:

Dymond ASD. Multiple objective optimization of an airfoil shape. [Internet] [Masters thesis]. University of Pretoria; 2011. [cited 2021 Jan 27]. Available from: http://hdl.handle.net/2263/22939.

Council of Science Editors:

Dymond ASD. Multiple objective optimization of an airfoil shape. [Masters Thesis]. University of Pretoria; 2011. Available from: http://hdl.handle.net/2263/22939

Kyoto University / 京都大学

16. Kaji, Hirotaka. Automotive Engine Calibration with Experiment-Based Evolutionary Multi-objective Optimization : 実験ベース進化的多目的最適化による自動車用エンジンの適合.

Degree: 博士(情報学), 2008, Kyoto University / 京都大学

URL: http://hdl.handle.net/2433/71034 ; http://dx.doi.org/10.14989/doctor.k14187

► The aim of this thesis is establishment of an overall framework of a novel control parameter optimization of automotive engine. Today, control parameters of an… (more)

▼ The aim of this thesis is establishment of an overall framework of a novel control parameter optimization of automotive engine. Today, control parameters of an automotive engine have to be adjusted adequately and simultaneously to achieve plural criteria such as environmental emissions, fuel-consumption and engine torque. This process is called 'engine calibration'. Because many electronic control devices have been adopted for engine to satisfy these objectives, the complexity of engine calibration is increasing year to year. Recent progress in automatic control and instrumentation provides a smart environment called Hardware In the Loop Simulation (HILS) for engine calibration. In addition, Response Surface Methodology (RSM) based on statistical model is currently employed as the optimization method. Nevertheless, this approach is complicated by adequate model selection, precise model construction, and close model validation to confirm the precision of the model output. To cope with these problems, we noticed experiment-based optimization via HILS environment based on Multi-objective Evolutionary Algorithms (MOEAs), that is expected to be a powerful optimization framework for real world problems such as engineering design, as another automatic calibration approach. In experiment-based optimization, the parameters of a real system are optimized directly by optimization techniques in real time through experimentation. In this thesis, this approach is called Experiment-Based Evolutionary Multi-objective Optimization (EBEMO) and it is proposed as a novel automatic engine calibration technique. This approach can release us from burdens of model selection, construction, and validation. When using this technique, calibration can be done immediately after specifications have been changed after optimization. Hence, EBEMO promises to be an effective approach to automatic engine calibration. However, since conventional MOEAs face several difficulties, it is not easy to apply it to real engines. On the one hand, deterioration factors of the search performance of MOEAs in real environments have to be considered. For example, the observation noise of sensors included in output interferes with convergence of MOEAs. In addition, transient response by parameter switching also has similar harmful effects. Moreover, the periodicity of control inputs increase the complexity of the problems. On the other hand, the search time of MOEAs in real environments has to reduce because MOEAs require a tremendous number of evaluations. While we can obtain many measurements with HILS, severe limitations in the number of fitness evaluations still exist because the real experiments need real-time evaluations. Therefore, it is difficult to obtain a set of Pareto optimal solutions in practical time with conventional MOEAs. Additionally, plural MOPs defined by plural operating conditions of map-based controllers has to be optimized. In this thesis, to overcome the difficulties and to make EBEMO using the HILS environment feasible, five techniques are…

Subjects/Keywords: evolutionary multi-objective optimization; engine calibration; experiment-based optimization

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APA (6^th Edition):

Kaji, H. (2008). Automotive Engine Calibration with Experiment-Based Evolutionary Multi-objective Optimization : 実験ベース進化的多目的最適化による自動車用エンジンの適合. (Thesis). Kyoto University / 京都大学. Retrieved from http://hdl.handle.net/2433/71034 ; http://dx.doi.org/10.14989/doctor.k14187

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Kaji, Hirotaka. “Automotive Engine Calibration with Experiment-Based Evolutionary Multi-objective Optimization : 実験ベース進化的多目的最適化による自動車用エンジンの適合.” 2008. Thesis, Kyoto University / 京都大学. Accessed January 27, 2021. http://hdl.handle.net/2433/71034 ; http://dx.doi.org/10.14989/doctor.k14187.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Kaji, Hirotaka. “Automotive Engine Calibration with Experiment-Based Evolutionary Multi-objective Optimization : 実験ベース進化的多目的最適化による自動車用エンジンの適合.” 2008. Web. 27 Jan 2021.

Vancouver:

Kaji H. Automotive Engine Calibration with Experiment-Based Evolutionary Multi-objective Optimization : 実験ベース進化的多目的最適化による自動車用エンジンの適合. [Internet] [Thesis]. Kyoto University / 京都大学; 2008. [cited 2021 Jan 27]. Available from: http://hdl.handle.net/2433/71034 ; http://dx.doi.org/10.14989/doctor.k14187.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Kaji H. Automotive Engine Calibration with Experiment-Based Evolutionary Multi-objective Optimization : 実験ベース進化的多目的最適化による自動車用エンジンの適合. [Thesis]. Kyoto University / 京都大学; 2008. Available from: http://hdl.handle.net/2433/71034 ; http://dx.doi.org/10.14989/doctor.k14187

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

17. Christian, Andrew W. A Multi-objective Evolutionary Optimization Approach to Procedural Noise Mitigation for Near-ground Aircraft.

Degree: 2013, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/17566

► This thesis demonstrates the viability and utility of using contemporary multi-objective evolutionary algorithms to minimize the noise impact of military aircraft on residential areas in… (more)

▼ This thesis demonstrates the viability and utility of using contemporary multi-objective evolutionary algorithms to minimize the noise impact of military aircraft on residential areas in the vicinity of airbases by suggesting novel flight procedures. That is, this thesis is searching for an algorithmic means of finding paths through the sky that aircraft can take which offer good performance in terms of noise as well as in terms of other possible flight metrics (e.g. fuel consumption). To do this, the current version of the US Navy noise-modelling program (NoiseMap 7) is combined with a recent multi-objective evolutionary algorithm (epsilon-MOEA). First, an overview of the pertinent mathematics of optimization is given, during which the uses of both an evolutionary algorithm and the multi-objective approach are defended. The basic acoustics of noise are discussed and a method for the aggregation of noise exposure across physically distributed populations is presented. The formulation of NoiseMap as a multi-objective optimization problem follows. A complication that makes the NoiseMap/epsilon-MOEA combination inefficient is discussed, and a solution is proposed and shown to be effective. Several other multi-objective optimization problems are presented which will be used for benchmarking and refining the optimization method. The population distribution of the Asheville, NC area is used as a hypothetical test case for this method. Several experimental optimizations are run serially so that the results of one inform the formulation of the next. The ultimate result is an optimization approach which, if appropriately parallelized on a modern desktop computer, can consistently produce subjectively accurate results within the span of 8 hours. The utility that is afforded to a decision maker by having these results is presented. Future directions for refinement and improvement of this method are discussed. Advisors/Committee Members: Victor Ward Sparrow, Thesis Advisor/Co-Advisor.

Subjects/Keywords: Acoustics; Aircraft noise; Community noise; Multi-objective optimization; Evolutionary optimization

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APA (6^th Edition):

Christian, A. W. (2013). A Multi-objective Evolutionary Optimization Approach to Procedural Noise Mitigation for Near-ground Aircraft. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/17566

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Christian, Andrew W. “A Multi-objective Evolutionary Optimization Approach to Procedural Noise Mitigation for Near-ground Aircraft.” 2013. Thesis, Penn State University. Accessed January 27, 2021. https://submit-etda.libraries.psu.edu/catalog/17566.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Christian, Andrew W. “A Multi-objective Evolutionary Optimization Approach to Procedural Noise Mitigation for Near-ground Aircraft.” 2013. Web. 27 Jan 2021.

Vancouver:

Christian AW. A Multi-objective Evolutionary Optimization Approach to Procedural Noise Mitigation for Near-ground Aircraft. [Internet] [Thesis]. Penn State University; 2013. [cited 2021 Jan 27]. Available from: https://submit-etda.libraries.psu.edu/catalog/17566.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Christian AW. A Multi-objective Evolutionary Optimization Approach to Procedural Noise Mitigation for Near-ground Aircraft. [Thesis]. Penn State University; 2013. Available from: https://submit-etda.libraries.psu.edu/catalog/17566

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Delft University of Technology

18. Goldschmeding, Marcel (author). Multi-Objective Trajectory Optimization for a Scaled Vehicle.

Degree: 2019, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:92853368-5495-438c-955f-b9b310dec2d5

► The introduction of control systems in the automotive industry has significantly increased safety. Improved control over the vehicle dynamics has been shown to contribute to… (more)

▼ The introduction of control systems in the automotive industry has significantly increased safety. Improved control over the vehicle dynamics has been shown to contribute to substantial reductions in the number of deaths and serious injuries resulting from road traffic crashes. The introduction of Electronic Stability Control yielded impressive improvement in vehicle stability. A meta-analysis revealed that a 49% reduction of single-vehicle accidents is realized. Recent research continues the development of a fully autonomously operating vehicle. The vehicle requires the ability to operate in all situations safely, in order to reach the highest level of automation. Vehicle performance should be guaranteed within, at and beyond the limits of friction. Previous research revealed that the unstable drift motion could enlarge the operating envelope of a vehicle. An extensive amount of research is dedicated to controlling a drift. The results show that control systems are increasingly capable of stabilizing a steady-state cornering scenario. The main limitation of these studies is that only a portion of the vehicle motion that is observed in reality can be considered to be steady-state motion. This thesis presents a multi-objective trajectory optimization which extends the steady-state analysis to a dynamic driving scenario. Based on experimental data obtained with a 1:10 scaled vehicle, accurate vehicle and tire models are derived. It is validated that the models closely mimic the dynamics of the scaled vehicle. In order to justify the use of drifting, the differences between stable and unstable driving equilibria are studied. The stability and controllability are assessed through the construction of the phase portraits and the computation of the Controllability Grammian. The findings, obtained under the assumption of steady-state conditions, are then validated in the dynamic driving scenario. A two-step optimization approach is presented. Spline optimization based on a simplified model is used to obtain initial conditions for a high fidelity model-based optimization. The scope is limited to a single corner, which is optimized under varying velocities and friction conditions. Under the assumption of steady-state conditions, it is found that the drift motion imposes various benefits over normal driving. Higher cornering velocities and therewith yaw rates can be achieved in a drift. Besides, the principles of tire saturation and force coupling allow for controlling the lateral and yaw dynamics of the vehicle through the rear longitudinal tire force. This increases the maneuverability of the vehicle. The results of the dynamic optimization extend the findings of the steady-state analysis. In the dynamic maneuvers, drifting is found to improve vehicle maneuverability at high velocities and in scenarios of low friction. The approach presented in this work forms a basis for studying the effects that drifting could have on vehicle motion in reality. The relevant aspects of vehicle motion are translated into a… Advisors/Committee Members: Hellendoorn, Hans (mentor), Corno, Matteo (mentor), Ferrari, Riccardo (graduation committee), Ferranti, Laura (graduation committee), Zheng, Yanggu (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Multi-objective optimization; Drifting; Splines; Parameter Identification; vehicle dynamics; Trajectory optimization

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APA (6^th Edition):

Goldschmeding, M. (. (2019). Multi-Objective Trajectory Optimization for a Scaled Vehicle. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:92853368-5495-438c-955f-b9b310dec2d5

Chicago Manual of Style (16^th Edition):

Goldschmeding, Marcel (author). “Multi-Objective Trajectory Optimization for a Scaled Vehicle.” 2019. Masters Thesis, Delft University of Technology. Accessed January 27, 2021. http://resolver.tudelft.nl/uuid:92853368-5495-438c-955f-b9b310dec2d5.

MLA Handbook (7^th Edition):

Goldschmeding, Marcel (author). “Multi-Objective Trajectory Optimization for a Scaled Vehicle.” 2019. Web. 27 Jan 2021.

Vancouver:

Goldschmeding M(. Multi-Objective Trajectory Optimization for a Scaled Vehicle. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Jan 27]. Available from: http://resolver.tudelft.nl/uuid:92853368-5495-438c-955f-b9b310dec2d5.

Council of Science Editors:

Goldschmeding M(. Multi-Objective Trajectory Optimization for a Scaled Vehicle. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:92853368-5495-438c-955f-b9b310dec2d5

Delft University of Technology

19. Bernal Mencia, Pablo (author). Co-orbital motion and its application to JAXA's MMX mission.

Degree: 2018, Delft University of Technology

URL: http://resolver.tudelft.nl/uuid:3378e0cf-7831-4432-a383-c9c5c8dbce2d

►

In the framework of JAXA's MMX mission to explore the Martian moon of Phobos, an analysis of the stability of three-dimensional quasi-satellite orbits in the… (more)

Subjects/Keywords: Astrodynamics; Orbit Design; Optimization; Multi-objective optimization; Periodic Orbits; Mars; Python

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APA (6^th Edition):

Bernal Mencia, P. (. (2018). Co-orbital motion and its application to JAXA's MMX mission. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:3378e0cf-7831-4432-a383-c9c5c8dbce2d

Chicago Manual of Style (16^th Edition):

Bernal Mencia, Pablo (author). “Co-orbital motion and its application to JAXA's MMX mission.” 2018. Masters Thesis, Delft University of Technology. Accessed January 27, 2021. http://resolver.tudelft.nl/uuid:3378e0cf-7831-4432-a383-c9c5c8dbce2d.

MLA Handbook (7^th Edition):

Bernal Mencia, Pablo (author). “Co-orbital motion and its application to JAXA's MMX mission.” 2018. Web. 27 Jan 2021.

Vancouver:

Bernal Mencia P(. Co-orbital motion and its application to JAXA's MMX mission. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Jan 27]. Available from: http://resolver.tudelft.nl/uuid:3378e0cf-7831-4432-a383-c9c5c8dbce2d.

Council of Science Editors:

Bernal Mencia P(. Co-orbital motion and its application to JAXA's MMX mission. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:3378e0cf-7831-4432-a383-c9c5c8dbce2d

University of Pretoria

20. Dymond, Antoine Smith Dryden. Multiple objective optimization of an airfoil shape .

Degree: 2011, University of Pretoria

URL: http://upetd.up.ac.za/thesis/available/etd-03022011-163939/

► An airfoil shape optimization problem with conflicting objectives is handled using two different multi-objective approaches. These are an a priori scalarization approach where the conflicting… (more)

Subjects/Keywords: Real-world optimization; Multi-objective optimization; Undefined regions; UCTD

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APA (6^th Edition):

Dymond, A. S. D. (2011). Multiple objective optimization of an airfoil shape . (Masters Thesis). University of Pretoria. Retrieved from http://upetd.up.ac.za/thesis/available/etd-03022011-163939/

Chicago Manual of Style (16^th Edition):

Dymond, Antoine Smith Dryden. “Multiple objective optimization of an airfoil shape .” 2011. Masters Thesis, University of Pretoria. Accessed January 27, 2021. http://upetd.up.ac.za/thesis/available/etd-03022011-163939/.

MLA Handbook (7^th Edition):

Dymond, Antoine Smith Dryden. “Multiple objective optimization of an airfoil shape .” 2011. Web. 27 Jan 2021.

Vancouver:

Dymond ASD. Multiple objective optimization of an airfoil shape . [Internet] [Masters thesis]. University of Pretoria; 2011. [cited 2021 Jan 27]. Available from: http://upetd.up.ac.za/thesis/available/etd-03022011-163939/.

Council of Science Editors:

Dymond ASD. Multiple objective optimization of an airfoil shape . [Masters Thesis]. University of Pretoria; 2011. Available from: http://upetd.up.ac.za/thesis/available/etd-03022011-163939/

Loughborough University

21. Le-Corre, Sam. Multi-objective optimization and analysis of nonlinear dynamic systems using genetic algorithms.

Degree: PhD, 2019, Loughborough University

URL: https://doi.org/10.26174/thesis.lboro.11950050.v1 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.804059

► The work in this thesis examines how complex dynamic systems can be improved and analysed using optimization techniques. A novel technique to systems analysis is… (more)

▼ The work in this thesis examines how complex dynamic systems can be improved and analysed using optimization techniques. A novel technique to systems analysis is presented and applied to a modern turbocharged, direct injection gasoline engine. A system-level view approach is taken which considers the whole system (engine and associated control strategy) to identify limitations imposed by the controls. Three key research gaps are identified and addressed. The first is the current lack of multi-objective optimization approaches applied to the engine calibration problem in a dynamic manner. Where optimization approaches are applied, they are either static, or massively constrained. A new route to engine calibration is shown to be possible with careful optimization problem definition. To this end, fast running neuro-fuzzy models and a combined system model including the controls strategy allows multi-objective approaches to be applied in an acceptable time-frame. Dynamic fragments which represent a wide range of engine conditions are used to generate optimal calibrations for the system using dynamic experiments rather than static, which is the current industry standard. The whole process; design of experiments for model design, model training, problem definition and optimization could feasibly be carried out in two weeks with further development. This represents a significant reduction from the current nominal twelve-week task. The process is also relatively autonomous; significant human input is not required to generate the calibrations, and instead the focus can be on the analysis of the candidate solutions. The second is the lack of applications of optimization techniques as an analysis tool to understand system behaviour and limitations. The analysis approach developed uses multiple subtly different problem formulations to gain unique perspectives on the system performance, and in doing so identifies the limitations. Two separate approaches, presented as case studies, are taken. The first examines improvement possible within the current controls' limitations, while the second identifies potential performance outside of the existing control strategy. Performance limitations of the system are linked to a simplification made in the controller design to allow the calibration task to be practical with conventional steady state mapping approaches. The multiple perspectives provided by the approach allows easy identification of the limits, and improved contextual information for understanding the optimization results. The final research gap is in the application of optimization to problems involving all four key aspects of complexity. These are; nonlinearity, problem size (number of objectives), dynamic problems, and robustness. The example problems are formulated in a way to include all four aspects. Non-dominated sorting genetic algorithm III (NSGA-III) is applied as a global solver to an inherently highly complex nonlinear problem. Multiple objectives, fuel consumption and NOX, are studied as well as the scalability of…

Subjects/Keywords: system analysis; Multi-Objective Optimization; applied optimization; Many-objective Optimization; Dynamic optimization; Genetic algorithms (GA); Dynamic systems approach; Engine calibration optimisation

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APA (6^th Edition):

Le-Corre, S. (2019). Multi-objective optimization and analysis of nonlinear dynamic systems using genetic algorithms. (Doctoral Dissertation). Loughborough University. Retrieved from https://doi.org/10.26174/thesis.lboro.11950050.v1 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.804059

Chicago Manual of Style (16^th Edition):

Le-Corre, Sam. “Multi-objective optimization and analysis of nonlinear dynamic systems using genetic algorithms.” 2019. Doctoral Dissertation, Loughborough University. Accessed January 27, 2021. https://doi.org/10.26174/thesis.lboro.11950050.v1 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.804059.

MLA Handbook (7^th Edition):

Le-Corre, Sam. “Multi-objective optimization and analysis of nonlinear dynamic systems using genetic algorithms.” 2019. Web. 27 Jan 2021.

Vancouver:

Le-Corre S. Multi-objective optimization and analysis of nonlinear dynamic systems using genetic algorithms. [Internet] [Doctoral dissertation]. Loughborough University; 2019. [cited 2021 Jan 27]. Available from: https://doi.org/10.26174/thesis.lboro.11950050.v1 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.804059.

Council of Science Editors:

Le-Corre S. Multi-objective optimization and analysis of nonlinear dynamic systems using genetic algorithms. [Doctoral Dissertation]. Loughborough University; 2019. Available from: https://doi.org/10.26174/thesis.lboro.11950050.v1 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.804059

22. Guzmán Pardo, María Alejandra. Técnicas de otimização baseadas em quimiotaxia de bactérias.

Degree: PhD, Projeto Mecânico, 2009, University of São Paulo

URL: http://www.teses.usp.br/teses/disponiveis/18/18146/tde-19012011-120319/ ;

►

Em sentido geral, a quimiotaxia é o movimento dirigido que desenvolvem alguns seres vivos em resposta aos gradientes químicos presentes no seu ambiente. Uma bactéria… (more)

▼

Em sentido geral, a quimiotaxia é o movimento dirigido que desenvolvem alguns seres vivos em resposta aos gradientes químicos presentes no seu ambiente. Uma bactéria é um organismo unicelular que usa a quimiotaxia como mecanismo de mobilização para encontrar os nutrientes de que precisa para sobreviver e para escapar de ambientes nocivos. Evoluída durante milhões de anos pela natureza, a quimiotaxia de bactérias é um processo altamente otimizado de busca e exploração em espaços desconhecidos. Graças aos avanços no campo da computação, as estratégias quimiotácticas das bactérias e sua excelente capacidade de busca podem ser modeladas, simuladas e emuladas para desenvolver métodos de otimização inspirados na natureza que sejam uma alternativa aos métodos já existentes. Neste trabalho, desenvolvem-se dois algoritmos baseados em estratégias quimiotácticas de bactérias: o BCBTOA (Bacterial Chemotaxis Based Topology Optimization Algorithm) e o BCMOA (Bacterial Chemotaxis Multiobjective Optimization Algorithm) os quais são um algoritmo de otimização topológica e um algoritmo de otimização multi-objetivo, respectivamente. O desempenho dos algoritmos é avaliado mediante a sua aplicação à solução de diversos problemas de prova e os resultados são comparados com os de outros algoritmos atualmente relevantes. O algoritmo de otimização multi-objetivo desenvolvido, também foi aplicado na solução de três problemas de otimização de projeto mecânico de eixos. Os resultados obtidos e os analise comparativos feitos, permitem concluir que os algoritmos desenvolvidos são altamente competitivos e demonstram o potencial do processo de quimiotaxia de bactérias como fonte de inspiração de algoritmos de otimização distribuída, contribuindo assim, a dar resposta à constante demanda por técnicas de otimização mais eficazes e robustas.

In general, chemotaxis is the biased movement developed by certain living organisms as a response to chemical gradients present in their environment. A bacterium is a unicellular organism that uses chemotaxis as a mechanism for mobilization that allows it to find nutrients needed to survive and to escape from harmful environments. Millions of years of natural evolution became bacterial chemotaxis a highly optimized process in searching and exploration of unknown spaces. Thanks to advances in the computing field, bacterial chemotactical strategies and its excellent ability in searching can be modeled, simulated and emulated developing bio-inspired optimization methods as alternatives to classical methods. Two algorithms based on bacterial chemotactical strategies were designed, developed and implemented in this work: i) the topology optimization algorithm, BCBTOA (Bacterial Chemotaxis Based Topology Optimization Algorithm) and ii) the multi-objective optimization algorithm, BCMOA (Bacterial Chemotaxis Multiobjective Optimization Algorithm). Algorithms performances were evaluated by their applications in the solution of benchmark problems and the results obtained were compared with other algorithms also relevant…

Advisors/Committee Members: Carvalho, Jonas de.

Subjects/Keywords: Bacterial chemotaxis; Multi-objective optimization; Otimização multi-objetivo; Otimização topológica; Quimiotaxia de bactérias; Topology optimization

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APA (6^th Edition):

Guzmán Pardo, M. A. (2009). Técnicas de otimização baseadas em quimiotaxia de bactérias. (Doctoral Dissertation). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/18/18146/tde-19012011-120319/ ;

Chicago Manual of Style (16^th Edition):

Guzmán Pardo, María Alejandra. “Técnicas de otimização baseadas em quimiotaxia de bactérias.” 2009. Doctoral Dissertation, University of São Paulo. Accessed January 27, 2021. http://www.teses.usp.br/teses/disponiveis/18/18146/tde-19012011-120319/ ;.

MLA Handbook (7^th Edition):

Guzmán Pardo, María Alejandra. “Técnicas de otimização baseadas em quimiotaxia de bactérias.” 2009. Web. 27 Jan 2021.

Vancouver:

Guzmán Pardo MA. Técnicas de otimização baseadas em quimiotaxia de bactérias. [Internet] [Doctoral dissertation]. University of São Paulo; 2009. [cited 2021 Jan 27]. Available from: http://www.teses.usp.br/teses/disponiveis/18/18146/tde-19012011-120319/ ;.

Council of Science Editors:

Guzmán Pardo MA. Técnicas de otimização baseadas em quimiotaxia de bactérias. [Doctoral Dissertation]. University of São Paulo; 2009. Available from: http://www.teses.usp.br/teses/disponiveis/18/18146/tde-19012011-120319/ ;

Penn State University

23. Nagar, Jogender. EFFICIENT AND ROBUST MULTI-OBJECTIVE OPTIMIZATION APPLIED TO PROBLEMS IN ELECTROSTATICS, ELECTROMAGNETICS AND OPTICS.

Degree: 2018, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/16027jun163

► Most design problems in electromagnetics and optics have multiple, often conflicting design objectives. A classic example is performance vs. price, where the designer is forced… (more)

▼ Most design problems in electromagnetics and optics have multiple, often conflicting design objectives. A classic example is performance vs. price, where the designer is forced to trade-off one desired objective for another. Multi-objective optimization (MOO) provides the designer with a set of solutions which show the intrinsic trade-offs between multiple conflicting objectives. This gives insight into the underlying physics of the problem and enables the designer to choose the best solution for a particular application. Despite its utility, MOO isn’t as popular in electromagnetics as it is in other fields such as economics, finance, mechanical and chemical engineering. The most popular commercial design tools do not support the MOO paradigm. This thesis will give an introduction and brief overview of different aspects of MOO, including methods for faster convergence and speed increases along with a variety of metrics for comparing the performance of different algorithms. Then a set of MOO algorithms will be described, with a focus on three state of the art optimizers, each of which has a unique design philosophy. BORG is an auto-adaptive genetic algorithm, the Multi-Objective Covariance Matrix Adaptation (MO-CMA) is an evolutionary strategy based on the popular single-objective CMA, and the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) is a scalarization algorithm which uses a Tchebysheff decomposition. The convergence, robustness and efficiency of these state-of-the-art optimizers has been studied exhaustively on simple test functions. In contrast, the algorithms here are tested on practical electromagnetic applications where the function evaluations are computationally expensive, making the convergence rate and sensitivity of these algorithms crucial factors in determining their feasibility. Another popular topic in the literature is in applying and comparing classical multi-objective optimizers (typically NSGA-II or one of its derivatives) on more complex practical problems. In contrast, the algorithms chosen for this study are state of the art and better suited for the extremely multi-modal and noisy objective landscapes encountered in electromagnetics. In order to study the algorithms, a comprehensive strategy will be described for comparing the quality of the three algorithms in the fairest manner possible. In addition, this thesis will provide guidelines on the appropriate optimizer to choose for a given problem and the recommended optimizer settings. The applications considered cover a diverse range of electromagnetics applications, including the optimization of an Electromagnetic Band Gap (EBG), a Vivaldi antenna and a PIFA antenna near a human head. Particular attention will be shown to the performance of a series of increasingly complicated stacked patch antenna operating in the RF. For this problem, a thorough statistical study will be performed on this model to determine the sensitivity of the optimizers to the intrinsic optimizer parameters, number of variables… Advisors/Committee Members: Douglas H. Werner, Dissertation Advisor/Co-Advisor, Douglas H. Werner, Committee Chair/Co-Chair, Pingjuan L. Werner, Committee Member, Viktor Pasko, Committee Member, Ram Rajagopalan, Outside Member.

Subjects/Keywords: Multi-objective optimization; optimization; electromagnetics; optics; gradient-index lens; antennas; electrostatics; topology optimization

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APA (6^th Edition):

Nagar, J. (2018). EFFICIENT AND ROBUST MULTI-OBJECTIVE OPTIMIZATION APPLIED TO PROBLEMS IN ELECTROSTATICS, ELECTROMAGNETICS AND OPTICS. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/16027jun163

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Nagar, Jogender. “EFFICIENT AND ROBUST MULTI-OBJECTIVE OPTIMIZATION APPLIED TO PROBLEMS IN ELECTROSTATICS, ELECTROMAGNETICS AND OPTICS.” 2018. Thesis, Penn State University. Accessed January 27, 2021. https://submit-etda.libraries.psu.edu/catalog/16027jun163.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Nagar, Jogender. “EFFICIENT AND ROBUST MULTI-OBJECTIVE OPTIMIZATION APPLIED TO PROBLEMS IN ELECTROSTATICS, ELECTROMAGNETICS AND OPTICS.” 2018. Web. 27 Jan 2021.

Vancouver:

Nagar J. EFFICIENT AND ROBUST MULTI-OBJECTIVE OPTIMIZATION APPLIED TO PROBLEMS IN ELECTROSTATICS, ELECTROMAGNETICS AND OPTICS. [Internet] [Thesis]. Penn State University; 2018. [cited 2021 Jan 27]. Available from: https://submit-etda.libraries.psu.edu/catalog/16027jun163.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nagar J. EFFICIENT AND ROBUST MULTI-OBJECTIVE OPTIMIZATION APPLIED TO PROBLEMS IN ELECTROSTATICS, ELECTROMAGNETICS AND OPTICS. [Thesis]. Penn State University; 2018. Available from: https://submit-etda.libraries.psu.edu/catalog/16027jun163

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of New South Wales

24. Singh, Hemant. Development of optimization methods to deal with current challenges in engineering design optimization.

Degree: Engineering & Information Technology, 2011, University of New South Wales

URL: http://handle.unsw.edu.au/1959.4/51426 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10110/SOURCE01?view=true

► In engineering design, optimization is customary, and often indispensable. Typical cases include minimization of drag for vehicles, minimization of weight for structures like buildings and… (more)

▼ In engineering design, optimization is customary, and often indispensable. Typical cases include minimization of drag for vehicles, minimization of weight for structures like buildings and bridges, maximization of power and lift for aircraft and rockets, minimization of fuel consumption for engines, etc. Therefore it comes as no surprise that development of fast and efficient optimization algorithms for engineering design is an actively pursued research area. In recent decades, metaheuristic algorithms have proven to be efficient, robust and versatile methods for numerical optimization. However, they usually need to evaluate a large number of candidate designs to find the optimum. This becomes prohibitive for engineering optimization problems in which each design evaluation may require computationally expensive analysis and, consequently, the optimization process may take much longer time than affordable. Considering that the number of design evaluations is a critical factor in overall optimization time, it is imperative to develop techniques to search for the optimum design using fewest evaluations possible. With this singular goal, this thesis investigates a range of domains in which existing approaches can be improved. Engineering problems are often highly non-linear, discontinuous, and non-differentiable, which rules out (or restricts) the applicability of analytical techniques for solving them. However, they exhibit additional attributes that prove challenging even to the existing metaheuristic techniques, thus making the search difficult and, consequently, creating a necessity for carrying out large numbers of evaluations. These include: (a) Constraints - constraints render a fraction (possibly large fraction) of the search space infeasible, making it hard to find the optimum and at times even a feasible design; (b) Large number of objectives - Pareto-dominance sorting, a commonly used technique in multi-objective optimization algorithms, is inadequate to solve problems with large numbers of objectives, a fact well reported in literature; (c) Large number of variables - the search space grows exponentially with the number of variables, which results in a corresponding increase in computational effort; and (d) Multiple models - For certain problems, there may be multiple candidate models to choose a solution from, with none of them being an obviously preferred one. In such a case, one may need to explore each one of them to find the global best. In this thesis, studies are conducted on each of these domains individually. Shortcomings of the existing methods are analyzed, and novel techniques are developed for efficiently handling constraints, large number of objectives/variables and multiple models. For effective constraint handling, conventional evolutionary algorithm is enhanced using a novel infeasibility driven ranking technique, while conventional simulated annealing algorithm is enhanced using an approximate descent direction coupled with dominance-based acceptance criteria.… Advisors/Committee Members: Ray, Tapabrata, Engineering & Information Technology, Australian Defence Force Academy, UNSW, Smith, Warren, Engineering & Information Technology, Australian Defence Force Academy, UNSW.

Subjects/Keywords: Coevolutionary algorithms; Engineering design optimization; Optimization algorithms; Metaheuristic algorithms; Multi-objective optimization algorithms

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APA (6^th Edition):

Singh, H. (2011). Development of optimization methods to deal with current challenges in engineering design optimization. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/51426 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10110/SOURCE01?view=true

Chicago Manual of Style (16^th Edition):

Singh, Hemant. “Development of optimization methods to deal with current challenges in engineering design optimization.” 2011. Doctoral Dissertation, University of New South Wales. Accessed January 27, 2021. http://handle.unsw.edu.au/1959.4/51426 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10110/SOURCE01?view=true.

MLA Handbook (7^th Edition):

Singh, Hemant. “Development of optimization methods to deal with current challenges in engineering design optimization.” 2011. Web. 27 Jan 2021.

Vancouver:

Singh H. Development of optimization methods to deal with current challenges in engineering design optimization. [Internet] [Doctoral dissertation]. University of New South Wales; 2011. [cited 2021 Jan 27]. Available from: http://handle.unsw.edu.au/1959.4/51426 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10110/SOURCE01?view=true.

Council of Science Editors:

Singh H. Development of optimization methods to deal with current challenges in engineering design optimization. [Doctoral Dissertation]. University of New South Wales; 2011. Available from: http://handle.unsw.edu.au/1959.4/51426 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10110/SOURCE01?view=true

Jönköping University

25. Amouzgar, Kaveh. Multi-objective optimization using Genetic Algorithms.

Degree: Engineering, 2012, Jönköping University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-19851

► In this thesis, the basic principles and concepts of single and multi-objective Genetic Algorithms (GA) are reviewed. Two algorithms, one for single objective and… (more)

Subjects/Keywords: Single Objective Optimization; Multi-objective Optimization; Constraint Handling; Hybrid Optimization; Evolutionary Algorithm; Genetic Algorithm; Pareto-Front; Domination

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Amouzgar, K. (2012). Multi-objective optimization using Genetic Algorithms. (Thesis). Jönköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-19851

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Amouzgar, Kaveh. “Multi-objective optimization using Genetic Algorithms.” 2012. Thesis, Jönköping University. Accessed January 27, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-19851.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Amouzgar, Kaveh. “Multi-objective optimization using Genetic Algorithms.” 2012. Web. 27 Jan 2021.

Vancouver:

Amouzgar K. Multi-objective optimization using Genetic Algorithms. [Internet] [Thesis]. Jönköping University; 2012. [cited 2021 Jan 27]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-19851.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Amouzgar K. Multi-objective optimization using Genetic Algorithms. [Thesis]. Jönköping University; 2012. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-19851

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

26. Pennada, Venkata Sai Teja. Solving Multiple Objective Optimization Problem using Multi-Agent Systems: A case in Logistics Management.

Degree: 2020, , Department of Computer Science

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20745

► Background: Multiple Objective Optimization problems(MOOPs) are common and evident in every field. Container port terminals are one of the fields in which MOOP occurs.… (more)

Subjects/Keywords: Multiple Objective Optimization Problem; Non-dominated Sorting Genetic Algorithm-II; Multi-agent systems; Multi-objective optimization model; Single-objective optimization model.; Computer Sciences; Datavetenskap (datalogi)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Pennada, V. S. T. (2020). Solving Multiple Objective Optimization Problem using Multi-Agent Systems: A case in Logistics Management. (Thesis). , Department of Computer Science. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20745

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Pennada, Venkata Sai Teja. “Solving Multiple Objective Optimization Problem using Multi-Agent Systems: A case in Logistics Management.” 2020. Thesis, , Department of Computer Science. Accessed January 27, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20745.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Pennada, Venkata Sai Teja. “Solving Multiple Objective Optimization Problem using Multi-Agent Systems: A case in Logistics Management.” 2020. Web. 27 Jan 2021.

Vancouver:

Pennada VST. Solving Multiple Objective Optimization Problem using Multi-Agent Systems: A case in Logistics Management. [Internet] [Thesis]. , Department of Computer Science; 2020. [cited 2021 Jan 27]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20745.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pennada VST. Solving Multiple Objective Optimization Problem using Multi-Agent Systems: A case in Logistics Management. [Thesis]. , Department of Computer Science; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:bth-20745

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

27. Chen, Shin-shou. A Study of Multi-objective Genetic Models for Stock Selection.

Degree: Master, Computer Science and Engineering, 2014, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0725114-101833

► Stock selection has long been recognized as a challenging and important task in finance. Recent advances in machine learning and data mining are leading to… (more)

Subjects/Keywords: genetic algorithms; stock selection; asset allocation; feature selection; multi-objective optimization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Chen, S. (2014). A Study of Multi-objective Genetic Models for Stock Selection. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0725114-101833

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Chen, Shin-shou. “A Study of Multi-objective Genetic Models for Stock Selection.” 2014. Thesis, NSYSU. Accessed January 27, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0725114-101833.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Chen, Shin-shou. “A Study of Multi-objective Genetic Models for Stock Selection.” 2014. Web. 27 Jan 2021.

Vancouver:

Chen S. A Study of Multi-objective Genetic Models for Stock Selection. [Internet] [Thesis]. NSYSU; 2014. [cited 2021 Jan 27]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0725114-101833.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chen S. A Study of Multi-objective Genetic Models for Stock Selection. [Thesis]. NSYSU; 2014. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0725114-101833

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

28. Huang , Yao-ting. Non-dominated Sorting Firefly Algorithm for Multi-objective Optimization.

Degree: Master, Computer Science and Engineering, 2015, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0806115-162831

► The so-called multi-objective optimization problem (MOP) has become a critical research subject because many multi-objective optimization problems exist in our daily life. Unlike solving a… (more)

Subjects/Keywords: NSGA-II; pareto optimality; multi-objective problems; firefly algorithm; functional optimization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Huang , Y. (2015). Non-dominated Sorting Firefly Algorithm for Multi-objective Optimization. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0806115-162831

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Huang , Yao-ting. “Non-dominated Sorting Firefly Algorithm for Multi-objective Optimization.” 2015. Thesis, NSYSU. Accessed January 27, 2021. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0806115-162831.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Huang , Yao-ting. “Non-dominated Sorting Firefly Algorithm for Multi-objective Optimization.” 2015. Web. 27 Jan 2021.

Vancouver:

Huang Y. Non-dominated Sorting Firefly Algorithm for Multi-objective Optimization. [Internet] [Thesis]. NSYSU; 2015. [cited 2021 Jan 27]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0806115-162831.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Huang Y. Non-dominated Sorting Firefly Algorithm for Multi-objective Optimization. [Thesis]. NSYSU; 2015. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0806115-162831

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

29. Elmusrati, Mohammed S. Radio Resource Scheduling and Smart Antennas in Cellular CDMA Communication Systems.

Degree: 2004, Helsinki University of Technology

URL: http://lib.tkk.fi/Diss/2004/isbn9512272202/

►

This thesis discusses two important subjects in multi-user wireless communication systems, radio resource scheduler (RRS) and smart antenna. RRS optimizes the available resources among users… (more)

▼

This thesis discusses two important subjects in multi-user wireless communication systems, radio resource scheduler (RRS) and smart antenna. RRS optimizes the available resources among users to increase the capacity and enhance the system performance. The RRS optimization procedure is based on the network conditions (link gain, interference, …) and the required quality of service (QoS) of each user. The CDMA system capacity and performance can be greatly enhanced by reducing the interferences. One of the techniques to reduce the interferences is by exploiting the spatial structure of the interferences. This could be done by using smart antennas which are the second subject of this thesis. The joining procedures of the smart antennas and RRS are discussed as well. Multi-Objective optimization approach is proposed to solve the radio resource scheduler problems. New algorithms are derived namely the Multi-Objective Distributed Power Control (MODPC) algorithm, Multi-Objective Distributed Power and Rate Control (MODPRC) algorithm, and Maximum Throughput and Minimum Power Control (MTMPC) algorithm. Other modified versions of these algorithms have been obtained such as Multi-Objective Totally Distributed Power and Rate Control (MOTDPRC) algorithm, which can be used when only one-bit quantized Carrier to Interference Ratio (CIR) is available. Kalman filter is proposed as a second technique to solve the RRS problem. The motivation to use Kalman filter is the known fact that Kalman filter is the optimum linear tracking device on the basis of second order statistics. The RRS is formulated in state space form. Two different formulations are introduced. New simple and efficient estimation of the CIR is presented. The method is used to construct a novel power control algorithm called Estimated Step Power Control (ESPC) algorithm. The smart antenna concepts and algorithms are discussed. New adaptation algorithm is proposed. It is called General Minimum Variance Distortionless Response (GMVDR) algorithm. The joining of MIMO smart antennas and radio resource scheduler is investigated. Kalman filter is suggested as a simple algorithm to join smart antenna and multi-rate power control in a new way. The performance of the RRS of CDMA cellular communication systems in the presence of smart antenna is studied.

Report / Helsinki University of Technology, Control Engineering Laboratory, ISSN 0356-0872; 142

Advisors/Committee Members: Helsinki University of Technology, Department of Automation and Systems Technology, Laboratory of Control Engineering.

Subjects/Keywords: CDMA; power control; RRS; smart antennas; multi-objective optimization; Kalman filters

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Elmusrati, M. S. (2004). Radio Resource Scheduling and Smart Antennas in Cellular CDMA Communication Systems. (Thesis). Helsinki University of Technology. Retrieved from http://lib.tkk.fi/Diss/2004/isbn9512272202/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Elmusrati, Mohammed S. “Radio Resource Scheduling and Smart Antennas in Cellular CDMA Communication Systems.” 2004. Thesis, Helsinki University of Technology. Accessed January 27, 2021. http://lib.tkk.fi/Diss/2004/isbn9512272202/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Elmusrati, Mohammed S. “Radio Resource Scheduling and Smart Antennas in Cellular CDMA Communication Systems.” 2004. Web. 27 Jan 2021.

Vancouver:

Elmusrati MS. Radio Resource Scheduling and Smart Antennas in Cellular CDMA Communication Systems. [Internet] [Thesis]. Helsinki University of Technology; 2004. [cited 2021 Jan 27]. Available from: http://lib.tkk.fi/Diss/2004/isbn9512272202/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Elmusrati MS. Radio Resource Scheduling and Smart Antennas in Cellular CDMA Communication Systems. [Thesis]. Helsinki University of Technology; 2004. Available from: http://lib.tkk.fi/Diss/2004/isbn9512272202/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Mississippi State University

30. Zhang, Jian. Techno-economic analysis and optimization of distributed energy systems.

Degree: PhD, Mechanical Engineering, 2018, Mississippi State University

URL: http://sun.library.msstate.edu/ETD-db/theses/available/etd-06222018-180048/ ;

► As a promising approach for sustainable development, distributed energy systems have receive increasing attention worldwide and have become a key topic explored by researchers… (more)

▼ As a promising approach for sustainable development, distributed energy systems have receive increasing attention worldwide and have become a key topic explored by researchers in the areas of building energy systems and smart grid. In line with this research trend, this dissertation presents a techno-economic analysis and optimization of distributed energy systems including combined heat and power (CHP), photovoltaics (PV), battery energy storage (BES), and thermal energy storage (TES) for commercial buildings. First, the techno-economic performance of the CHP system is analyzed and evaluated for four building types including hospital, large office, large hotel, and secondary school, located in different U.S. regions. The energy consumption of each building is obtained by EnergyPlus simulation software. The simulation models of CHP system are established for each building type. From the simulation results, the payback period (PBP) of the CHP system in different locations is calculated. The parameters that have an influence on the PBP of the CHP system are analyzed. Second, PV system and integrated PV and BES (PV-BES) system are investigated for several commercial building types, respectively. The effects of the variation in key parameters, such as PV system capacity, capital cost of PV, sell back ratio, battery capacity, and capital cost of battery, on the performance of PV and/or PV-BES system are explored. Finally, subsystems in previous chapters (CHP, PV, and BES) along with TES system are integrated together based on a proposed control strategy to meet the electric and thermal energy demand of commercial buildings (i.e., hospital and large hotel). A multi-objective particle swarm optimization (PSO) is conducted to determine the optimal size of each subsystem with the objective to minimize the payback period and maximize the reduction of carbon dioxide emissions. The results reveal how the key factors affect the performance of distributed energy system and demonstrate the proposed optimization can be effectively utilized to obtain an optimized design of distributed energy systems that can get a tradeoff between the environmental and economic impacts for different buildings. Advisors/Committee Members: Heejin Cho (committee member), Rogelio Luck (committee member), Pedro J. Mago (committee member), Alta Knizley (committee member).

Subjects/Keywords: payback period; multi-objective optimization; distributed energy systems; Techno-economic analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Zhang, J. (2018). Techno-economic analysis and optimization of distributed energy systems. (Doctoral Dissertation). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-06222018-180048/ ;

Chicago Manual of Style (16^th Edition):

Zhang, Jian. “Techno-economic analysis and optimization of distributed energy systems.” 2018. Doctoral Dissertation, Mississippi State University. Accessed January 27, 2021. http://sun.library.msstate.edu/ETD-db/theses/available/etd-06222018-180048/ ;.

MLA Handbook (7^th Edition):

Zhang, Jian. “Techno-economic analysis and optimization of distributed energy systems.” 2018. Web. 27 Jan 2021.

Vancouver:

Zhang J. Techno-economic analysis and optimization of distributed energy systems. [Internet] [Doctoral dissertation]. Mississippi State University; 2018. [cited 2021 Jan 27]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-06222018-180048/ ;.

Council of Science Editors:

Zhang J. Techno-economic analysis and optimization of distributed energy systems. [Doctoral Dissertation]. Mississippi State University; 2018. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-06222018-180048/ ;

Open Access Theses and Dissertations