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You searched for subject:(constrained optimization). Showing records 1 – 30 of 258 total matches.

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University of Oxford

1. Desmaison, Alban. Optimization for, and by, machine learning.

Degree: PhD, 2019, University of Oxford

Optimization and machine learning are both extremely active research topics. In this thesis, we explore problems at the intersection of the two fields. In particular,… (more)

Subjects/Keywords: Machine learning; Constrained optimization

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APA (6th Edition):

Desmaison, A. (2019). Optimization for, and by, machine learning. (Doctoral Dissertation). University of Oxford. Retrieved from http://ora.ox.ac.uk/objects/uuid:7b9b387a-fcce-425c-8186-5d161789a52a ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.813610

Chicago Manual of Style (16th Edition):

Desmaison, Alban. “Optimization for, and by, machine learning.” 2019. Doctoral Dissertation, University of Oxford. Accessed March 09, 2021. http://ora.ox.ac.uk/objects/uuid:7b9b387a-fcce-425c-8186-5d161789a52a ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.813610.

MLA Handbook (7th Edition):

Desmaison, Alban. “Optimization for, and by, machine learning.” 2019. Web. 09 Mar 2021.

Vancouver:

Desmaison A. Optimization for, and by, machine learning. [Internet] [Doctoral dissertation]. University of Oxford; 2019. [cited 2021 Mar 09]. Available from: http://ora.ox.ac.uk/objects/uuid:7b9b387a-fcce-425c-8186-5d161789a52a ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.813610.

Council of Science Editors:

Desmaison A. Optimization for, and by, machine learning. [Doctoral Dissertation]. University of Oxford; 2019. Available from: http://ora.ox.ac.uk/objects/uuid:7b9b387a-fcce-425c-8186-5d161789a52a ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.813610


University of Adelaide

2. Bonyadi, Mohammadreza. Particle swarm optimization: theoretical analysis, modifications, and applications to constrained optimization problems.

Degree: 2015, University of Adelaide

 This is a PhD thesis by publication. It includes five journal papers, three of them already published, and two submitted for publication in a very… (more)

Subjects/Keywords: optimization; convergence; transformation invariance; constrained optimization

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APA (6th Edition):

Bonyadi, M. (2015). Particle swarm optimization: theoretical analysis, modifications, and applications to constrained optimization problems. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/92599

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

Chicago Manual of Style (16th Edition):

Bonyadi, Mohammadreza. “Particle swarm optimization: theoretical analysis, modifications, and applications to constrained optimization problems.” 2015. Thesis, University of Adelaide. Accessed March 09, 2021. http://hdl.handle.net/2440/92599.

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

MLA Handbook (7th Edition):

Bonyadi, Mohammadreza. “Particle swarm optimization: theoretical analysis, modifications, and applications to constrained optimization problems.” 2015. Web. 09 Mar 2021.

Vancouver:

Bonyadi M. Particle swarm optimization: theoretical analysis, modifications, and applications to constrained optimization problems. [Internet] [Thesis]. University of Adelaide; 2015. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/2440/92599.

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

Council of Science Editors:

Bonyadi M. Particle swarm optimization: theoretical analysis, modifications, and applications to constrained optimization problems. [Thesis]. University of Adelaide; 2015. Available from: http://hdl.handle.net/2440/92599

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


Rice University

3. Geldermans, Peter. Accelerated PDE Constrained Optimization using Direct Solvers.

Degree: MA, Engineering, 2018, Rice University

 In this thesis, I propose a method to reduce the cost of computing solutions to optimization problems governed by partial differential equations (PDEs). Standard second… (more)

Subjects/Keywords: PDE constrained optimization; direct solvers; fast solvers

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APA (6th Edition):

Geldermans, P. (2018). Accelerated PDE Constrained Optimization using Direct Solvers. (Masters Thesis). Rice University. Retrieved from http://hdl.handle.net/1911/105485

Chicago Manual of Style (16th Edition):

Geldermans, Peter. “Accelerated PDE Constrained Optimization using Direct Solvers.” 2018. Masters Thesis, Rice University. Accessed March 09, 2021. http://hdl.handle.net/1911/105485.

MLA Handbook (7th Edition):

Geldermans, Peter. “Accelerated PDE Constrained Optimization using Direct Solvers.” 2018. Web. 09 Mar 2021.

Vancouver:

Geldermans P. Accelerated PDE Constrained Optimization using Direct Solvers. [Internet] [Masters thesis]. Rice University; 2018. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/1911/105485.

Council of Science Editors:

Geldermans P. Accelerated PDE Constrained Optimization using Direct Solvers. [Masters Thesis]. Rice University; 2018. Available from: http://hdl.handle.net/1911/105485


University of Illinois – Urbana-Champaign

4. Salazar De Troya, Miguel Angel A. Adaptive mesh refinement in topology optimization.

Degree: PhD, Mechanical Engineering, 2019, University of Illinois – Urbana-Champaign

 This dissertation presents developments in stress constrained topology optimization with Adaptive Mesh Refinement (AMR). Regions with stress concentrations dominate the optimized design. As such, we… (more)

Subjects/Keywords: topology; optimization; adaptive; mesh; refinement; stress; constrained

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APA (6th Edition):

Salazar De Troya, M. A. A. (2019). Adaptive mesh refinement in topology optimization. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/104776

Chicago Manual of Style (16th Edition):

Salazar De Troya, Miguel Angel A. “Adaptive mesh refinement in topology optimization.” 2019. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed March 09, 2021. http://hdl.handle.net/2142/104776.

MLA Handbook (7th Edition):

Salazar De Troya, Miguel Angel A. “Adaptive mesh refinement in topology optimization.” 2019. Web. 09 Mar 2021.

Vancouver:

Salazar De Troya MAA. Adaptive mesh refinement in topology optimization. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2019. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/2142/104776.

Council of Science Editors:

Salazar De Troya MAA. Adaptive mesh refinement in topology optimization. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2019. Available from: http://hdl.handle.net/2142/104776


Oklahoma State University

5. Govindarajan, Anand. Optimization of Processes for Sustainability.

Degree: School of Chemical Engineering, 2011, Oklahoma State University

 This research is focused on developing a methodology to optimize processes for sustainability. To design a sustainable process that addresses economic, environmental and social concerns… (more)

Subjects/Keywords: chemical processes; constrained; multiobjective; optimization; sustainability; weighted

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APA (6th Edition):

Govindarajan, A. (2011). Optimization of Processes for Sustainability. (Thesis). Oklahoma State University. Retrieved from http://hdl.handle.net/11244/9634

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

Chicago Manual of Style (16th Edition):

Govindarajan, Anand. “Optimization of Processes for Sustainability.” 2011. Thesis, Oklahoma State University. Accessed March 09, 2021. http://hdl.handle.net/11244/9634.

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

MLA Handbook (7th Edition):

Govindarajan, Anand. “Optimization of Processes for Sustainability.” 2011. Web. 09 Mar 2021.

Vancouver:

Govindarajan A. Optimization of Processes for Sustainability. [Internet] [Thesis]. Oklahoma State University; 2011. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/11244/9634.

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

Council of Science Editors:

Govindarajan A. Optimization of Processes for Sustainability. [Thesis]. Oklahoma State University; 2011. Available from: http://hdl.handle.net/11244/9634

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


Penn State University

6. Kang, Bosung. Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP).

Degree: 2015, Penn State University

 Estimating the disturbance or clutter covariance is a centrally important problem in radar space time adaptive processing (STAP) since estimation of the disturbance or interference… (more)

Subjects/Keywords: convex optimization; STAP; radar signal processing; constrained optimization; detection and estimation

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APA (6th Edition):

Kang, B. (2015). Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP). (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/26539

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

Chicago Manual of Style (16th Edition):

Kang, Bosung. “Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP).” 2015. Thesis, Penn State University. Accessed March 09, 2021. https://submit-etda.libraries.psu.edu/catalog/26539.

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

MLA Handbook (7th Edition):

Kang, Bosung. “Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP).” 2015. Web. 09 Mar 2021.

Vancouver:

Kang B. Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP). [Internet] [Thesis]. Penn State University; 2015. [cited 2021 Mar 09]. Available from: https://submit-etda.libraries.psu.edu/catalog/26539.

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

Council of Science Editors:

Kang B. Robust Covariance Matrix Estimation for Radar Space-Time Adaptive Processing (STAP). [Thesis]. Penn State University; 2015. Available from: https://submit-etda.libraries.psu.edu/catalog/26539

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


Rice University

7. Markowski, Mae. Newton-Based Methods for Smoothed Risk-Averse PDE-Constrained Optimization Problems.

Degree: MA, Engineering, 2019, Rice University

 This thesis introduces a modification for traditional, Newton-based methods to improve the efficiency of solving smoothed, risk-averse PDE-constrained optimization problems arising from optimal control applications.… (more)

Subjects/Keywords: Optimization under uncertainty; Conditional Value-at-Risk; PDE-Constrained Optimization

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APA (6th Edition):

Markowski, M. (2019). Newton-Based Methods for Smoothed Risk-Averse PDE-Constrained Optimization Problems. (Masters Thesis). Rice University. Retrieved from http://hdl.handle.net/1911/107436

Chicago Manual of Style (16th Edition):

Markowski, Mae. “Newton-Based Methods for Smoothed Risk-Averse PDE-Constrained Optimization Problems.” 2019. Masters Thesis, Rice University. Accessed March 09, 2021. http://hdl.handle.net/1911/107436.

MLA Handbook (7th Edition):

Markowski, Mae. “Newton-Based Methods for Smoothed Risk-Averse PDE-Constrained Optimization Problems.” 2019. Web. 09 Mar 2021.

Vancouver:

Markowski M. Newton-Based Methods for Smoothed Risk-Averse PDE-Constrained Optimization Problems. [Internet] [Masters thesis]. Rice University; 2019. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/1911/107436.

Council of Science Editors:

Markowski M. Newton-Based Methods for Smoothed Risk-Averse PDE-Constrained Optimization Problems. [Masters Thesis]. Rice University; 2019. Available from: http://hdl.handle.net/1911/107436


Georgia Tech

8. Torrico Palacios, Alfredo Ignacio. Resource allocation and subset selection: new approaches at the interface between discrete and continuous optimization.

Degree: PhD, Industrial and Systems Engineering, 2019, Georgia Tech

 Resource allocation and subset selection are two relevant classes of problems in the core of combinatorial optimization. Over the past decade, there has been an… (more)

Subjects/Keywords: Combinatorial optimization; Online optimization; Online bipartite matching; Constrained submodular maximization

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APA (6th Edition):

Torrico Palacios, A. I. (2019). Resource allocation and subset selection: new approaches at the interface between discrete and continuous optimization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61720

Chicago Manual of Style (16th Edition):

Torrico Palacios, Alfredo Ignacio. “Resource allocation and subset selection: new approaches at the interface between discrete and continuous optimization.” 2019. Doctoral Dissertation, Georgia Tech. Accessed March 09, 2021. http://hdl.handle.net/1853/61720.

MLA Handbook (7th Edition):

Torrico Palacios, Alfredo Ignacio. “Resource allocation and subset selection: new approaches at the interface between discrete and continuous optimization.” 2019. Web. 09 Mar 2021.

Vancouver:

Torrico Palacios AI. Resource allocation and subset selection: new approaches at the interface between discrete and continuous optimization. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/1853/61720.

Council of Science Editors:

Torrico Palacios AI. Resource allocation and subset selection: new approaches at the interface between discrete and continuous optimization. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61720


University of Washington

9. Dueri, Daniel Alejandro. Real-time Optimization in Aerospace Systems.

Degree: PhD, 2019, University of Washington

 Algorithm design for autonomous vehicles has been attracting immense research interest, and with the proliferation of self-driving cars, autonomous drone delivery systems, and the increasing… (more)

Subjects/Keywords: constrained optimization; convex optimization; optimal control theory; real-time optimization; Aerospace engineering; Aeronautics and astronautics

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APA (6th Edition):

Dueri, D. A. (2019). Real-time Optimization in Aerospace Systems. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/43279

Chicago Manual of Style (16th Edition):

Dueri, Daniel Alejandro. “Real-time Optimization in Aerospace Systems.” 2019. Doctoral Dissertation, University of Washington. Accessed March 09, 2021. http://hdl.handle.net/1773/43279.

MLA Handbook (7th Edition):

Dueri, Daniel Alejandro. “Real-time Optimization in Aerospace Systems.” 2019. Web. 09 Mar 2021.

Vancouver:

Dueri DA. Real-time Optimization in Aerospace Systems. [Internet] [Doctoral dissertation]. University of Washington; 2019. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/1773/43279.

Council of Science Editors:

Dueri DA. Real-time Optimization in Aerospace Systems. [Doctoral Dissertation]. University of Washington; 2019. Available from: http://hdl.handle.net/1773/43279


University of Arizona

10. Chernikov, Dmitry. PDE Constrained Optimization in Stochastic and Deterministic Problems of Multiphysics and Finance .

Degree: 2017, University of Arizona

 In this dissertation we investigate methods of solving various optimization problems with PDE constraints, i.e. optimization problems that have a system of partial differential equations… (more)

Subjects/Keywords: adjoint differentiation; automatic differentiation; multiphysics; nonlinear optimization; optimization of portfolio of options; PDE-constrained optimization

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APA (6th Edition):

Chernikov, D. (2017). PDE Constrained Optimization in Stochastic and Deterministic Problems of Multiphysics and Finance . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/626368

Chicago Manual of Style (16th Edition):

Chernikov, Dmitry. “PDE Constrained Optimization in Stochastic and Deterministic Problems of Multiphysics and Finance .” 2017. Doctoral Dissertation, University of Arizona. Accessed March 09, 2021. http://hdl.handle.net/10150/626368.

MLA Handbook (7th Edition):

Chernikov, Dmitry. “PDE Constrained Optimization in Stochastic and Deterministic Problems of Multiphysics and Finance .” 2017. Web. 09 Mar 2021.

Vancouver:

Chernikov D. PDE Constrained Optimization in Stochastic and Deterministic Problems of Multiphysics and Finance . [Internet] [Doctoral dissertation]. University of Arizona; 2017. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/10150/626368.

Council of Science Editors:

Chernikov D. PDE Constrained Optimization in Stochastic and Deterministic Problems of Multiphysics and Finance . [Doctoral Dissertation]. University of Arizona; 2017. Available from: http://hdl.handle.net/10150/626368


University of Texas – Austin

11. Nasir, Yusuf, M.S. in Engineering. Derivative-free techniques for optimal development of conventional and unconventional reservoirs.

Degree: MSin Engineering, Petroleum Engineering, 2018, University of Texas – Austin

 The cyclic nature of oil price and the incentive from an optimal field development strategy has made the need for the development and management of… (more)

Subjects/Keywords: Derivative-free optimization; Constrained optimization; Differential evolution; Reservoir simulation; Well placement; Production optimization

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APA (6th Edition):

Nasir, Yusuf, M. S. i. E. (2018). Derivative-free techniques for optimal development of conventional and unconventional reservoirs. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/69254

Chicago Manual of Style (16th Edition):

Nasir, Yusuf, M S in Engineering. “Derivative-free techniques for optimal development of conventional and unconventional reservoirs.” 2018. Masters Thesis, University of Texas – Austin. Accessed March 09, 2021. http://hdl.handle.net/2152/69254.

MLA Handbook (7th Edition):

Nasir, Yusuf, M S in Engineering. “Derivative-free techniques for optimal development of conventional and unconventional reservoirs.” 2018. Web. 09 Mar 2021.

Vancouver:

Nasir, Yusuf MSiE. Derivative-free techniques for optimal development of conventional and unconventional reservoirs. [Internet] [Masters thesis]. University of Texas – Austin; 2018. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/2152/69254.

Council of Science Editors:

Nasir, Yusuf MSiE. Derivative-free techniques for optimal development of conventional and unconventional reservoirs. [Masters Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/69254


Georgia Tech

12. Boob, Digvijay Pravin. Convex and structured nonconvex optimization for modern machine learning: Complexity and algorithms.

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

 In this thesis, we investigate various optimization problems motivated by applications in modern-day machine learning. In the first part, we look at the computational complexity… (more)

Subjects/Keywords: Computational complexity; NP-hardness; Function constrained optimization; Convex composite optimization; Nonconvex composite optimization; Stochastic optimization; Sparse-constrained nonconvex optimization; Packing and covering LPs

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APA (6th Edition):

Boob, D. P. (2020). Convex and structured nonconvex optimization for modern machine learning: Complexity and algorithms. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63673

Chicago Manual of Style (16th Edition):

Boob, Digvijay Pravin. “Convex and structured nonconvex optimization for modern machine learning: Complexity and algorithms.” 2020. Doctoral Dissertation, Georgia Tech. Accessed March 09, 2021. http://hdl.handle.net/1853/63673.

MLA Handbook (7th Edition):

Boob, Digvijay Pravin. “Convex and structured nonconvex optimization for modern machine learning: Complexity and algorithms.” 2020. Web. 09 Mar 2021.

Vancouver:

Boob DP. Convex and structured nonconvex optimization for modern machine learning: Complexity and algorithms. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/1853/63673.

Council of Science Editors:

Boob DP. Convex and structured nonconvex optimization for modern machine learning: Complexity and algorithms. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/63673

13. Vanitha M. Investigations on non convex economic load dispatch problem and solution through constrained optimization techniques;.

Degree: non convex economic load dispatch problem and solution through constrained optimization techniques, 2014, Anna University

In the modern scenario, the electric power generation is very newlineessential and is a major criterion for all power related applications. There are newlinevarious resources… (more)

Subjects/Keywords: Constrained optimization techniques; Economic Load Dispatch; Electrical engineering

Page 1

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APA (6th Edition):

M, V. (2014). Investigations on non convex economic load dispatch problem and solution through constrained optimization techniques;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/16071

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

Chicago Manual of Style (16th Edition):

M, Vanitha. “Investigations on non convex economic load dispatch problem and solution through constrained optimization techniques;.” 2014. Thesis, Anna University. Accessed March 09, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/16071.

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

MLA Handbook (7th Edition):

M, Vanitha. “Investigations on non convex economic load dispatch problem and solution through constrained optimization techniques;.” 2014. Web. 09 Mar 2021.

Vancouver:

M V. Investigations on non convex economic load dispatch problem and solution through constrained optimization techniques;. [Internet] [Thesis]. Anna University; 2014. [cited 2021 Mar 09]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/16071.

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

Council of Science Editors:

M V. Investigations on non convex economic load dispatch problem and solution through constrained optimization techniques;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/16071

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

14. Narmathabanu R. Genetic algorithmbased preventiveAnd corrective control approachesFor power system securityEnhancement;.

Degree: Genetic algorithmbased preventiveAnd corrective control approachesFor power system securityEnhancement, 2014, Anna University

The ability of a power system to withstand the occurrence of newlinecontingencies like outage of transmission line or generator without any newlineuntoward incident is called… (more)

Subjects/Keywords: Genetic Algorithm; Security Constrained Optimal Power Flow; Several optimization techniques

Page 1

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APA (6th Edition):

R, N. (2014). Genetic algorithmbased preventiveAnd corrective control approachesFor power system securityEnhancement;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/30145

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

Chicago Manual of Style (16th Edition):

R, Narmathabanu. “Genetic algorithmbased preventiveAnd corrective control approachesFor power system securityEnhancement;.” 2014. Thesis, Anna University. Accessed March 09, 2021. http://shodhganga.inflibnet.ac.in/handle/10603/30145.

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

MLA Handbook (7th Edition):

R, Narmathabanu. “Genetic algorithmbased preventiveAnd corrective control approachesFor power system securityEnhancement;.” 2014. Web. 09 Mar 2021.

Vancouver:

R N. Genetic algorithmbased preventiveAnd corrective control approachesFor power system securityEnhancement;. [Internet] [Thesis]. Anna University; 2014. [cited 2021 Mar 09]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/30145.

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

Council of Science Editors:

R N. Genetic algorithmbased preventiveAnd corrective control approachesFor power system securityEnhancement;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/30145

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


Queens University

15. Peter, Samuel. Constrained extremum-seeking control in discrete-time with application to liquefier unit power minimization .

Degree: Chemical Engineering, 2016, Queens University

 Given the increasing complexity of engineering systems, difficulties are often met in developing models that describe these systems accurately. If the model is used for… (more)

Subjects/Keywords: Liquefier Optimization ; Constrained ESC ; time-varying ESC ; ESC

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APA (6th Edition):

Peter, S. (2016). Constrained extremum-seeking control in discrete-time with application to liquefier unit power minimization . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/14287

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

Chicago Manual of Style (16th Edition):

Peter, Samuel. “Constrained extremum-seeking control in discrete-time with application to liquefier unit power minimization .” 2016. Thesis, Queens University. Accessed March 09, 2021. http://hdl.handle.net/1974/14287.

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

MLA Handbook (7th Edition):

Peter, Samuel. “Constrained extremum-seeking control in discrete-time with application to liquefier unit power minimization .” 2016. Web. 09 Mar 2021.

Vancouver:

Peter S. Constrained extremum-seeking control in discrete-time with application to liquefier unit power minimization . [Internet] [Thesis]. Queens University; 2016. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/1974/14287.

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

Council of Science Editors:

Peter S. Constrained extremum-seeking control in discrete-time with application to liquefier unit power minimization . [Thesis]. Queens University; 2016. Available from: http://hdl.handle.net/1974/14287

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


Texas A&M University

16. Geng, Xinbo. Power System Operations with Probabilistic Guarantees.

Degree: PhD, Electrical Engineering, 2019, Texas A&M University

 This study is motivated by the fact that uncertainties from deepening penetration of renewable energy resources have posed critical challenges to the secure and reliable… (more)

Subjects/Keywords: Chance-constrained optimization; power system operation; unit commitment; economic dispatch.

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APA (6th Edition):

Geng, X. (2019). Power System Operations with Probabilistic Guarantees. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/188735

Chicago Manual of Style (16th Edition):

Geng, Xinbo. “Power System Operations with Probabilistic Guarantees.” 2019. Doctoral Dissertation, Texas A&M University. Accessed March 09, 2021. http://hdl.handle.net/1969.1/188735.

MLA Handbook (7th Edition):

Geng, Xinbo. “Power System Operations with Probabilistic Guarantees.” 2019. Web. 09 Mar 2021.

Vancouver:

Geng X. Power System Operations with Probabilistic Guarantees. [Internet] [Doctoral dissertation]. Texas A&M University; 2019. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/1969.1/188735.

Council of Science Editors:

Geng X. Power System Operations with Probabilistic Guarantees. [Doctoral Dissertation]. Texas A&M University; 2019. Available from: http://hdl.handle.net/1969.1/188735


University of Southern California

17. Wang, Yi. Towards energy efficient mobile sensing.

Degree: PhD, Electrical Engineering, 2011, University of Southern California

 Mobile device based urban sensing, participatory sensing, and user activity recognition can provide rich contextual information for mobile applications such as social networking and location… (more)

Subjects/Keywords: constrained stochastic optimization; energy efficiency; mobile sensing; state estimation

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APA (6th Edition):

Wang, Y. (2011). Towards energy efficient mobile sensing. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/445526/rec/7537

Chicago Manual of Style (16th Edition):

Wang, Yi. “Towards energy efficient mobile sensing.” 2011. Doctoral Dissertation, University of Southern California. Accessed March 09, 2021. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/445526/rec/7537.

MLA Handbook (7th Edition):

Wang, Yi. “Towards energy efficient mobile sensing.” 2011. Web. 09 Mar 2021.

Vancouver:

Wang Y. Towards energy efficient mobile sensing. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2021 Mar 09]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/445526/rec/7537.

Council of Science Editors:

Wang Y. Towards energy efficient mobile sensing. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/445526/rec/7537


Curtin University of Technology

18. Yu, Changjun. A study of optimization and optimal control computation : exact penalty function approach .

Degree: 2012, Curtin University of Technology

 In this thesis, We propose new computational algorithms and methods for solving four classes of constrained optimization and optimal control problems. In Chapter 1, we… (more)

Subjects/Keywords: new computational algorithms; constrained optimization and optimal control; constraint violation

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APA (6th Edition):

Yu, C. (2012). A study of optimization and optimal control computation : exact penalty function approach . (Thesis). Curtin University of Technology. Retrieved from http://hdl.handle.net/20.500.11937/2387

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

Chicago Manual of Style (16th Edition):

Yu, Changjun. “A study of optimization and optimal control computation : exact penalty function approach .” 2012. Thesis, Curtin University of Technology. Accessed March 09, 2021. http://hdl.handle.net/20.500.11937/2387.

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

MLA Handbook (7th Edition):

Yu, Changjun. “A study of optimization and optimal control computation : exact penalty function approach .” 2012. Web. 09 Mar 2021.

Vancouver:

Yu C. A study of optimization and optimal control computation : exact penalty function approach . [Internet] [Thesis]. Curtin University of Technology; 2012. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/20.500.11937/2387.

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

Council of Science Editors:

Yu C. A study of optimization and optimal control computation : exact penalty function approach . [Thesis]. Curtin University of Technology; 2012. Available from: http://hdl.handle.net/20.500.11937/2387

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


Louisiana State University

19. Ciftci, Okan. Microgrid Energy Management with Flexibility Constraints: A Data-Driven Solution Method.

Degree: MSEE, Power and Energy, 2017, Louisiana State University

  Microgrid energy management is a challenging and important problem in modern power systems. Several deterministic and stochastic models have been proposed in the literature… (more)

Subjects/Keywords: microgrid; energy management; energy storage; flexibility; data-driven; chance-constrained optimization

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

APA (6th Edition):

Ciftci, O. (2017). Microgrid Energy Management with Flexibility Constraints: A Data-Driven Solution Method. (Masters Thesis). Louisiana State University. Retrieved from https://digitalcommons.lsu.edu/gradschool_theses/4351

Chicago Manual of Style (16th Edition):

Ciftci, Okan. “Microgrid Energy Management with Flexibility Constraints: A Data-Driven Solution Method.” 2017. Masters Thesis, Louisiana State University. Accessed March 09, 2021. https://digitalcommons.lsu.edu/gradschool_theses/4351.

MLA Handbook (7th Edition):

Ciftci, Okan. “Microgrid Energy Management with Flexibility Constraints: A Data-Driven Solution Method.” 2017. Web. 09 Mar 2021.

Vancouver:

Ciftci O. Microgrid Energy Management with Flexibility Constraints: A Data-Driven Solution Method. [Internet] [Masters thesis]. Louisiana State University; 2017. [cited 2021 Mar 09]. Available from: https://digitalcommons.lsu.edu/gradschool_theses/4351.

Council of Science Editors:

Ciftci O. Microgrid Energy Management with Flexibility Constraints: A Data-Driven Solution Method. [Masters Thesis]. Louisiana State University; 2017. Available from: https://digitalcommons.lsu.edu/gradschool_theses/4351


California State University – Sacramento

20. Helmand, Azizullah. Security constrained economic dispatch using shift factors.

Degree: MS, Electrical and Electronic Engineering, 2020, California State University – Sacramento

 This report will investigate a simplified rendition of market bid determination against a network topology. This project uses a variation of linear programming to minimize… (more)

Subjects/Keywords: Power flow analysis; Grid operations; Optimization techniques; Security constrained unit commitment

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

APA (6th Edition):

Helmand, A. (2020). Security constrained economic dispatch using shift factors. (Masters Thesis). California State University – Sacramento. Retrieved from http://hdl.handle.net/10211.3/216495

Chicago Manual of Style (16th Edition):

Helmand, Azizullah. “Security constrained economic dispatch using shift factors.” 2020. Masters Thesis, California State University – Sacramento. Accessed March 09, 2021. http://hdl.handle.net/10211.3/216495.

MLA Handbook (7th Edition):

Helmand, Azizullah. “Security constrained economic dispatch using shift factors.” 2020. Web. 09 Mar 2021.

Vancouver:

Helmand A. Security constrained economic dispatch using shift factors. [Internet] [Masters thesis]. California State University – Sacramento; 2020. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/10211.3/216495.

Council of Science Editors:

Helmand A. Security constrained economic dispatch using shift factors. [Masters Thesis]. California State University – Sacramento; 2020. Available from: http://hdl.handle.net/10211.3/216495


Georgia Tech

21. Zhou, Zhiqiang. Theory and applications of first-order methods for convex optimization with function constraints.

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

 This dissertation focuses on the development of efficient first-order methods for function constrained convex optimization and their applications in a few different areas, including healthcare,… (more)

Subjects/Keywords: First-order methods; Function constrained optimization; Machine learning

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APA (6th Edition):

Zhou, Z. (2020). Theory and applications of first-order methods for convex optimization with function constraints. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63664

Chicago Manual of Style (16th Edition):

Zhou, Zhiqiang. “Theory and applications of first-order methods for convex optimization with function constraints.” 2020. Doctoral Dissertation, Georgia Tech. Accessed March 09, 2021. http://hdl.handle.net/1853/63664.

MLA Handbook (7th Edition):

Zhou, Zhiqiang. “Theory and applications of first-order methods for convex optimization with function constraints.” 2020. Web. 09 Mar 2021.

Vancouver:

Zhou Z. Theory and applications of first-order methods for convex optimization with function constraints. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/1853/63664.

Council of Science Editors:

Zhou Z. Theory and applications of first-order methods for convex optimization with function constraints. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/63664


University of New South Wales

22. Hamza, Noha. Search Techniques for Evolutionary Constrained Optimization.

Degree: Engineering & Information Technology, 2016, University of New South Wales

 Solving Constrained Optimization Problems (COPs) has been an important research topic in the optimization, operation research, and computer science domains. Over the last few decades,… (more)

Subjects/Keywords: differential evolution; Evolutionary algorithms; constrained optimization; constraint consensus; constraint-handling

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APA (6th Edition):

Hamza, N. (2016). Search Techniques for Evolutionary Constrained Optimization. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/56426 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:40694/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Hamza, Noha. “Search Techniques for Evolutionary Constrained Optimization.” 2016. Doctoral Dissertation, University of New South Wales. Accessed March 09, 2021. http://handle.unsw.edu.au/1959.4/56426 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:40694/SOURCE02?view=true.

MLA Handbook (7th Edition):

Hamza, Noha. “Search Techniques for Evolutionary Constrained Optimization.” 2016. Web. 09 Mar 2021.

Vancouver:

Hamza N. Search Techniques for Evolutionary Constrained Optimization. [Internet] [Doctoral dissertation]. University of New South Wales; 2016. [cited 2021 Mar 09]. Available from: http://handle.unsw.edu.au/1959.4/56426 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:40694/SOURCE02?view=true.

Council of Science Editors:

Hamza N. Search Techniques for Evolutionary Constrained Optimization. [Doctoral Dissertation]. University of New South Wales; 2016. Available from: http://handle.unsw.edu.au/1959.4/56426 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:40694/SOURCE02?view=true


University of New South Wales

23. Sallam, Karam. A Study of Function Landscape and Search Space with Evolutionary Algorithms.

Degree: Engineering & Information Technology, 2018, University of New South Wales

Optimization techniques are used extensively to solve many real-world decision making problems which have different characteristics and mathematical properties that make the process of finding… (more)

Subjects/Keywords: differential evolution; Evolutionary algorithms; constrained optimization; landscape analysis; reduced search space

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APA (6th Edition):

Sallam, K. (2018). A Study of Function Landscape and Search Space with Evolutionary Algorithms. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/59803 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49835/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Sallam, Karam. “A Study of Function Landscape and Search Space with Evolutionary Algorithms.” 2018. Doctoral Dissertation, University of New South Wales. Accessed March 09, 2021. http://handle.unsw.edu.au/1959.4/59803 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49835/SOURCE02?view=true.

MLA Handbook (7th Edition):

Sallam, Karam. “A Study of Function Landscape and Search Space with Evolutionary Algorithms.” 2018. Web. 09 Mar 2021.

Vancouver:

Sallam K. A Study of Function Landscape and Search Space with Evolutionary Algorithms. [Internet] [Doctoral dissertation]. University of New South Wales; 2018. [cited 2021 Mar 09]. Available from: http://handle.unsw.edu.au/1959.4/59803 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49835/SOURCE02?view=true.

Council of Science Editors:

Sallam K. A Study of Function Landscape and Search Space with Evolutionary Algorithms. [Doctoral Dissertation]. University of New South Wales; 2018. Available from: http://handle.unsw.edu.au/1959.4/59803 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49835/SOURCE02?view=true


University of Texas – Austin

24. -6943-657X. Optimal spatiotemporal resource allocation in public health and renewable energy.

Degree: PhD, Operations Research & Industrial Engineering, 2016, University of Texas – Austin

 Optimizing the spatiotemporal allocation and distribution of a limited number of critical resources is a pervasive problem, concerning both government agencies and private companies. This… (more)

Subjects/Keywords: Stochastic optimization; Chance-constrained programming; Pumped-hydroelectric system; Public health

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APA (6th Edition):

-6943-657X. (2016). Optimal spatiotemporal resource allocation in public health and renewable energy. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/44589

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-6943-657X. “Optimal spatiotemporal resource allocation in public health and renewable energy.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed March 09, 2021. http://hdl.handle.net/2152/44589.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-6943-657X. “Optimal spatiotemporal resource allocation in public health and renewable energy.” 2016. Web. 09 Mar 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-6943-657X. Optimal spatiotemporal resource allocation in public health and renewable energy. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/2152/44589.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-6943-657X. Optimal spatiotemporal resource allocation in public health and renewable energy. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/44589

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


Virginia Tech

25. Hunter, Susan R. Sampling Laws for Stochastically Constrained Simulation Optimization on Finite Sets.

Degree: PhD, Industrial and Systems Engineering, 2011, Virginia Tech

 Consider the context of selecting an optimal system from among a finite set of competing systems, based on a â stochasticâ objective function and subject(more)

Subjects/Keywords: optimal allocation; constrained simulation optimization; ranking and selection

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APA (6th Edition):

Hunter, S. R. (2011). Sampling Laws for Stochastically Constrained Simulation Optimization on Finite Sets. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/39742

Chicago Manual of Style (16th Edition):

Hunter, Susan R. “Sampling Laws for Stochastically Constrained Simulation Optimization on Finite Sets.” 2011. Doctoral Dissertation, Virginia Tech. Accessed March 09, 2021. http://hdl.handle.net/10919/39742.

MLA Handbook (7th Edition):

Hunter, Susan R. “Sampling Laws for Stochastically Constrained Simulation Optimization on Finite Sets.” 2011. Web. 09 Mar 2021.

Vancouver:

Hunter SR. Sampling Laws for Stochastically Constrained Simulation Optimization on Finite Sets. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/10919/39742.

Council of Science Editors:

Hunter SR. Sampling Laws for Stochastically Constrained Simulation Optimization on Finite Sets. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/39742


University of New South Wales

26. Hu, Wei. VALUATION OF NON-TRANSFERABLE AND NON-HEDGEABLE CONTINGENT CLAIMS AND AN EXECUTIVE STOCK OPTIONS IMPLEMENTATION.

Degree: Banking & Finance, 2011, University of New South Wales

 As traditional contingent claims valuation methods do not apply to non-transferable and non-hedgeable contingent claims, recent proliferation of such claims creates the need for the… (more)

Subjects/Keywords: Stochastic discount factor; ESO; Constrained portfolio optimization; Credit risk; Reload option

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APA (6th Edition):

Hu, W. (2011). VALUATION OF NON-TRANSFERABLE AND NON-HEDGEABLE CONTINGENT CLAIMS AND AN EXECUTIVE STOCK OPTIONS IMPLEMENTATION. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/51924 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10594/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Hu, Wei. “VALUATION OF NON-TRANSFERABLE AND NON-HEDGEABLE CONTINGENT CLAIMS AND AN EXECUTIVE STOCK OPTIONS IMPLEMENTATION.” 2011. Doctoral Dissertation, University of New South Wales. Accessed March 09, 2021. http://handle.unsw.edu.au/1959.4/51924 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10594/SOURCE02?view=true.

MLA Handbook (7th Edition):

Hu, Wei. “VALUATION OF NON-TRANSFERABLE AND NON-HEDGEABLE CONTINGENT CLAIMS AND AN EXECUTIVE STOCK OPTIONS IMPLEMENTATION.” 2011. Web. 09 Mar 2021.

Vancouver:

Hu W. VALUATION OF NON-TRANSFERABLE AND NON-HEDGEABLE CONTINGENT CLAIMS AND AN EXECUTIVE STOCK OPTIONS IMPLEMENTATION. [Internet] [Doctoral dissertation]. University of New South Wales; 2011. [cited 2021 Mar 09]. Available from: http://handle.unsw.edu.au/1959.4/51924 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10594/SOURCE02?view=true.

Council of Science Editors:

Hu W. VALUATION OF NON-TRANSFERABLE AND NON-HEDGEABLE CONTINGENT CLAIMS AND AN EXECUTIVE STOCK OPTIONS IMPLEMENTATION. [Doctoral Dissertation]. University of New South Wales; 2011. Available from: http://handle.unsw.edu.au/1959.4/51924 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10594/SOURCE02?view=true


University of New South Wales

27. Hamza, Noha. Hybridizing constraint consensus methods with evolutionary algorithms for constrained optimization.

Degree: Engineering & Information Technology Canberra, 2012, University of New South Wales

 Solving Constrained Optimization Problems (COPs) has been an important research topic in the optimization, operation research, and computer science domains. In COPs, an optimal solution… (more)

Subjects/Keywords: Genetic Algorithms; Evolutionary Algorithms; Constrained Optimization; Differential Evolution

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APA (6th Edition):

Hamza, N. (2012). Hybridizing constraint consensus methods with evolutionary algorithms for constrained optimization. (Masters Thesis). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/52091 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10761/SOURCE01?view=true

Chicago Manual of Style (16th Edition):

Hamza, Noha. “Hybridizing constraint consensus methods with evolutionary algorithms for constrained optimization.” 2012. Masters Thesis, University of New South Wales. Accessed March 09, 2021. http://handle.unsw.edu.au/1959.4/52091 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10761/SOURCE01?view=true.

MLA Handbook (7th Edition):

Hamza, Noha. “Hybridizing constraint consensus methods with evolutionary algorithms for constrained optimization.” 2012. Web. 09 Mar 2021.

Vancouver:

Hamza N. Hybridizing constraint consensus methods with evolutionary algorithms for constrained optimization. [Internet] [Masters thesis]. University of New South Wales; 2012. [cited 2021 Mar 09]. Available from: http://handle.unsw.edu.au/1959.4/52091 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10761/SOURCE01?view=true.

Council of Science Editors:

Hamza N. Hybridizing constraint consensus methods with evolutionary algorithms for constrained optimization. [Masters Thesis]. University of New South Wales; 2012. Available from: http://handle.unsw.edu.au/1959.4/52091 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10761/SOURCE01?view=true


University of Toronto

28. Mahmood, Rafid. Learning to Solve Optimization Problems with Hidden Components: Applications in Automated Treatment Planning.

Degree: PhD, 2020, University of Toronto

 Designing optimization models that capture decision-maker preferences typically requires guidance from domain experts. We can instead employ machine learning (ML) to design contextual optimization models… (more)

Subjects/Keywords: constrained optimization; machine learning; medical decision-making; radiation therapy; 0796

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APA (6th Edition):

Mahmood, R. (2020). Learning to Solve Optimization Problems with Hidden Components: Applications in Automated Treatment Planning. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/103339

Chicago Manual of Style (16th Edition):

Mahmood, Rafid. “Learning to Solve Optimization Problems with Hidden Components: Applications in Automated Treatment Planning.” 2020. Doctoral Dissertation, University of Toronto. Accessed March 09, 2021. http://hdl.handle.net/1807/103339.

MLA Handbook (7th Edition):

Mahmood, Rafid. “Learning to Solve Optimization Problems with Hidden Components: Applications in Automated Treatment Planning.” 2020. Web. 09 Mar 2021.

Vancouver:

Mahmood R. Learning to Solve Optimization Problems with Hidden Components: Applications in Automated Treatment Planning. [Internet] [Doctoral dissertation]. University of Toronto; 2020. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/1807/103339.

Council of Science Editors:

Mahmood R. Learning to Solve Optimization Problems with Hidden Components: Applications in Automated Treatment Planning. [Doctoral Dissertation]. University of Toronto; 2020. Available from: http://hdl.handle.net/1807/103339


Duke University

29. Sridhar, Aarthi. Modeling and Probabilistic Optimization of Rolling Isolation System for Seismic Hazard Mitigation .

Degree: 2019, Duke University

  A new model for Rolling Isolation Systems(RIS) is developed using Gauss's Principle of Least Constraint (GPLC). Gauss Principle of Least Constraint is a versatile… (more)

Subjects/Keywords: Civil engineering; Constrained Dynamics; Earthquake Hazard Mitigation; Optimization; Rolling Isolation System

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APA (6th Edition):

Sridhar, A. (2019). Modeling and Probabilistic Optimization of Rolling Isolation System for Seismic Hazard Mitigation . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/19840

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

Chicago Manual of Style (16th Edition):

Sridhar, Aarthi. “Modeling and Probabilistic Optimization of Rolling Isolation System for Seismic Hazard Mitigation .” 2019. Thesis, Duke University. Accessed March 09, 2021. http://hdl.handle.net/10161/19840.

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

MLA Handbook (7th Edition):

Sridhar, Aarthi. “Modeling and Probabilistic Optimization of Rolling Isolation System for Seismic Hazard Mitigation .” 2019. Web. 09 Mar 2021.

Vancouver:

Sridhar A. Modeling and Probabilistic Optimization of Rolling Isolation System for Seismic Hazard Mitigation . [Internet] [Thesis]. Duke University; 2019. [cited 2021 Mar 09]. Available from: http://hdl.handle.net/10161/19840.

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

Council of Science Editors:

Sridhar A. Modeling and Probabilistic Optimization of Rolling Isolation System for Seismic Hazard Mitigation . [Thesis]. Duke University; 2019. Available from: http://hdl.handle.net/10161/19840

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


Penn State University

30. Mohammadzadeh Jasour, Ashkan. Convex Approximation of Chance Constrained Optimization Problems: Application in System and Control.

Degree: 2017, Penn State University

 This dissertation concentrates on chance constrained optimization problems and their application in systems and control area. In “chance optimization” problems, we aim at maximizing the… (more)

Subjects/Keywords: Chance Constrained; Convex Optimization; Semidefinite Programming; Measure and Moments; Polynomials; Sum of Squares Optimization; Duality

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APA (6th Edition):

Mohammadzadeh Jasour, A. (2017). Convex Approximation of Chance Constrained Optimization Problems: Application in System and Control. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/13313aim5346

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

Chicago Manual of Style (16th Edition):

Mohammadzadeh Jasour, Ashkan. “Convex Approximation of Chance Constrained Optimization Problems: Application in System and Control.” 2017. Thesis, Penn State University. Accessed March 09, 2021. https://submit-etda.libraries.psu.edu/catalog/13313aim5346.

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

MLA Handbook (7th Edition):

Mohammadzadeh Jasour, Ashkan. “Convex Approximation of Chance Constrained Optimization Problems: Application in System and Control.” 2017. Web. 09 Mar 2021.

Vancouver:

Mohammadzadeh Jasour A. Convex Approximation of Chance Constrained Optimization Problems: Application in System and Control. [Internet] [Thesis]. Penn State University; 2017. [cited 2021 Mar 09]. Available from: https://submit-etda.libraries.psu.edu/catalog/13313aim5346.

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

Council of Science Editors:

Mohammadzadeh Jasour A. Convex Approximation of Chance Constrained Optimization Problems: Application in System and Control. [Thesis]. Penn State University; 2017. Available from: https://submit-etda.libraries.psu.edu/catalog/13313aim5346

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

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