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You searched for subject:(Robust optimization). Showing records 1 – 30 of 522 total matches.

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Università della Svizzera italiana

1. Mutsanas, Nikos. Approximability of precedence constrained and robust scheduling problems.

Degree: 2010, Università della Svizzera italiana

 We study the approximability of scheduling problems in different contexts. We first give a short introduction to the field of scheduling theory and present a… (more)

Subjects/Keywords: Robust optimization

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APA (6th Edition):

Mutsanas, N. (2010). Approximability of precedence constrained and robust scheduling problems. (Thesis). Università della Svizzera italiana. Retrieved from http://doc.rero.ch/record/18217

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):

Mutsanas, Nikos. “Approximability of precedence constrained and robust scheduling problems.” 2010. Thesis, Università della Svizzera italiana. Accessed May 11, 2021. http://doc.rero.ch/record/18217.

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

MLA Handbook (7th Edition):

Mutsanas, Nikos. “Approximability of precedence constrained and robust scheduling problems.” 2010. Web. 11 May 2021.

Vancouver:

Mutsanas N. Approximability of precedence constrained and robust scheduling problems. [Internet] [Thesis]. Università della Svizzera italiana; 2010. [cited 2021 May 11]. Available from: http://doc.rero.ch/record/18217.

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

Council of Science Editors:

Mutsanas N. Approximability of precedence constrained and robust scheduling problems. [Thesis]. Università della Svizzera italiana; 2010. Available from: http://doc.rero.ch/record/18217

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


Delft University of Technology

2. Chiscop, Irina (author). A robust optimization approach to synchromodal container transportation.

Degree: 2018, Delft University of Technology

 This thesis addresses synchromodal planning at operational level from the perspective of a logistics service provider. The existing infrastructure and the transportation activities are studied… (more)

Subjects/Keywords: Synchromodal; Robust; Optimization

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APA (6th Edition):

Chiscop, I. (. (2018). A robust optimization approach to synchromodal container transportation. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:f2e84a4a-aef4-45b5-a9d0-e97afd17b04b

Chicago Manual of Style (16th Edition):

Chiscop, Irina (author). “A robust optimization approach to synchromodal container transportation.” 2018. Masters Thesis, Delft University of Technology. Accessed May 11, 2021. http://resolver.tudelft.nl/uuid:f2e84a4a-aef4-45b5-a9d0-e97afd17b04b.

MLA Handbook (7th Edition):

Chiscop, Irina (author). “A robust optimization approach to synchromodal container transportation.” 2018. Web. 11 May 2021.

Vancouver:

Chiscop I(. A robust optimization approach to synchromodal container transportation. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 May 11]. Available from: http://resolver.tudelft.nl/uuid:f2e84a4a-aef4-45b5-a9d0-e97afd17b04b.

Council of Science Editors:

Chiscop I(. A robust optimization approach to synchromodal container transportation. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:f2e84a4a-aef4-45b5-a9d0-e97afd17b04b


University of Minnesota

3. Moulton, Jeffrey. Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity.

Degree: PhD, Mathematics, 2016, University of Minnesota

 Decision makers often must consider many different possible future scenarios when they make a decision. A manager must choose inventory levels to maximize profit when… (more)

Subjects/Keywords: clustering; distributionally robust optimization; fragmentation; newsvendor; robust

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APA (6th Edition):

Moulton, J. (2016). Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/182165

Chicago Manual of Style (16th Edition):

Moulton, Jeffrey. “Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity.” 2016. Doctoral Dissertation, University of Minnesota. Accessed May 11, 2021. http://hdl.handle.net/11299/182165.

MLA Handbook (7th Edition):

Moulton, Jeffrey. “Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity.” 2016. Web. 11 May 2021.

Vancouver:

Moulton J. Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2021 May 11]. Available from: http://hdl.handle.net/11299/182165.

Council of Science Editors:

Moulton J. Robust Fragmentation: A Data-Driven Approach to Decision-Making Under Distributional Ambiguity. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/182165


Oregon State University

4. Mokhtari, Zahra. Incorporating Uncertainty in Truckload Relay Network Design.

Degree: PhD, Industrial Engineering, 2017, Oregon State University

 In a relay network for full truckload (TL) transportation, facilities known as relay points (RPs) serve as exchange points where truck drivers can exchange trailers.… (more)

Subjects/Keywords: truckload transportation; Robust optimization

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APA (6th Edition):

Mokhtari, Z. (2017). Incorporating Uncertainty in Truckload Relay Network Design. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/60591

Chicago Manual of Style (16th Edition):

Mokhtari, Zahra. “Incorporating Uncertainty in Truckload Relay Network Design.” 2017. Doctoral Dissertation, Oregon State University. Accessed May 11, 2021. http://hdl.handle.net/1957/60591.

MLA Handbook (7th Edition):

Mokhtari, Zahra. “Incorporating Uncertainty in Truckload Relay Network Design.” 2017. Web. 11 May 2021.

Vancouver:

Mokhtari Z. Incorporating Uncertainty in Truckload Relay Network Design. [Internet] [Doctoral dissertation]. Oregon State University; 2017. [cited 2021 May 11]. Available from: http://hdl.handle.net/1957/60591.

Council of Science Editors:

Mokhtari Z. Incorporating Uncertainty in Truckload Relay Network Design. [Doctoral Dissertation]. Oregon State University; 2017. Available from: http://hdl.handle.net/1957/60591


Hong Kong University of Science and Technology

5. Pan, Lingyi. Assignment in ridesharing with uncertainties.

Degree: 2020, Hong Kong University of Science and Technology

 We propose a robust model to study the multi-period assignment problem in ridesharing in which both demand and travel time are uncertain. We consider finite… (more)

Subjects/Keywords: Ridesharing ; Uncertainty ; Robust optimization

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APA (6th Edition):

Pan, L. (2020). Assignment in ridesharing with uncertainties. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-108676 ; https://doi.org/10.14711/thesis-991012872965803412 ; http://repository.ust.hk/ir/bitstream/1783.1-108676/1/th_redirect.html

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):

Pan, Lingyi. “Assignment in ridesharing with uncertainties.” 2020. Thesis, Hong Kong University of Science and Technology. Accessed May 11, 2021. http://repository.ust.hk/ir/Record/1783.1-108676 ; https://doi.org/10.14711/thesis-991012872965803412 ; http://repository.ust.hk/ir/bitstream/1783.1-108676/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Pan, Lingyi. “Assignment in ridesharing with uncertainties.” 2020. Web. 11 May 2021.

Vancouver:

Pan L. Assignment in ridesharing with uncertainties. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2020. [cited 2021 May 11]. Available from: http://repository.ust.hk/ir/Record/1783.1-108676 ; https://doi.org/10.14711/thesis-991012872965803412 ; http://repository.ust.hk/ir/bitstream/1783.1-108676/1/th_redirect.html.

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

Council of Science Editors:

Pan L. Assignment in ridesharing with uncertainties. [Thesis]. Hong Kong University of Science and Technology; 2020. Available from: http://repository.ust.hk/ir/Record/1783.1-108676 ; https://doi.org/10.14711/thesis-991012872965803412 ; http://repository.ust.hk/ir/bitstream/1783.1-108676/1/th_redirect.html

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


University of Ottawa

6. Mahdavi, Roshanak. An Adjustable Robust Optimization Approach to Multi-objective Personnel Scheduling Under Uncertain Demand: A Case Study at a Pathology Department.

Degree: MSc, Gestion / Management, 2020, University of Ottawa

 In this thesis, we address a multi-objective personnel scheduling problem where personnel’s workload is uncertain and propose a two-stage robust modelling approach with demand uncertainty.… (more)

Subjects/Keywords: Personnel Scheduling; Robust Optimization

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APA (6th Edition):

Mahdavi, R. (2020). An Adjustable Robust Optimization Approach to Multi-objective Personnel Scheduling Under Uncertain Demand: A Case Study at a Pathology Department. (Masters Thesis). University of Ottawa. Retrieved from http://dx.doi.org/10.20381/ruor-25202

Chicago Manual of Style (16th Edition):

Mahdavi, Roshanak. “An Adjustable Robust Optimization Approach to Multi-objective Personnel Scheduling Under Uncertain Demand: A Case Study at a Pathology Department.” 2020. Masters Thesis, University of Ottawa. Accessed May 11, 2021. http://dx.doi.org/10.20381/ruor-25202.

MLA Handbook (7th Edition):

Mahdavi, Roshanak. “An Adjustable Robust Optimization Approach to Multi-objective Personnel Scheduling Under Uncertain Demand: A Case Study at a Pathology Department.” 2020. Web. 11 May 2021.

Vancouver:

Mahdavi R. An Adjustable Robust Optimization Approach to Multi-objective Personnel Scheduling Under Uncertain Demand: A Case Study at a Pathology Department. [Internet] [Masters thesis]. University of Ottawa; 2020. [cited 2021 May 11]. Available from: http://dx.doi.org/10.20381/ruor-25202.

Council of Science Editors:

Mahdavi R. An Adjustable Robust Optimization Approach to Multi-objective Personnel Scheduling Under Uncertain Demand: A Case Study at a Pathology Department. [Masters Thesis]. University of Ottawa; 2020. Available from: http://dx.doi.org/10.20381/ruor-25202


University of Texas – Austin

7. Sathasivan, Kanthimathi. Optimizing cross-dock operations under uncertainty.

Degree: PhD, Civil Engineering, 2011, University of Texas – Austin

 Cross-docking is an important transportation logistics strategy in supply chain management which reduces transportation costs, inventory holding costs, order-picking costs and response time. Careful planning… (more)

Subjects/Keywords: Cross-docking; Uncertainty; Robust optimization

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APA (6th Edition):

Sathasivan, K. (2011). Optimizing cross-dock operations under uncertainty. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2011-12-4589

Chicago Manual of Style (16th Edition):

Sathasivan, Kanthimathi. “Optimizing cross-dock operations under uncertainty.” 2011. Doctoral Dissertation, University of Texas – Austin. Accessed May 11, 2021. http://hdl.handle.net/2152/ETD-UT-2011-12-4589.

MLA Handbook (7th Edition):

Sathasivan, Kanthimathi. “Optimizing cross-dock operations under uncertainty.” 2011. Web. 11 May 2021.

Vancouver:

Sathasivan K. Optimizing cross-dock operations under uncertainty. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2011. [cited 2021 May 11]. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4589.

Council of Science Editors:

Sathasivan K. Optimizing cross-dock operations under uncertainty. [Doctoral Dissertation]. University of Texas – Austin; 2011. Available from: http://hdl.handle.net/2152/ETD-UT-2011-12-4589


University of Toronto

8. Kaw, Neal. Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems.

Degree: 2017, University of Toronto

Most inverse optimization models impute unspecified parameters of an objective function to make an observed solution optimal for a given optimization problem. In this thesis,… (more)

Subjects/Keywords: Inverse optimization; Nonlinear programming; Robust optimization; 0796

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APA (6th Edition):

Kaw, N. (2017). Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/79311

Chicago Manual of Style (16th Edition):

Kaw, Neal. “Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems.” 2017. Masters Thesis, University of Toronto. Accessed May 11, 2021. http://hdl.handle.net/1807/79311.

MLA Handbook (7th Edition):

Kaw, Neal. “Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems.” 2017. Web. 11 May 2021.

Vancouver:

Kaw N. Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems. [Internet] [Masters thesis]. University of Toronto; 2017. [cited 2021 May 11]. Available from: http://hdl.handle.net/1807/79311.

Council of Science Editors:

Kaw N. Inverse linear optimization for the recovery of constraint parameters in robust and non-robust problems. [Masters Thesis]. University of Toronto; 2017. Available from: http://hdl.handle.net/1807/79311


Columbia University

9. Kang, Yang. Distributionally Robust Optimization and its Applications in Machine Learning.

Degree: 2017, Columbia University

 The goal of Distributionally Robust Optimization (DRO) is to minimize the cost of running a stochastic system, under the assumption that an adversary can replace… (more)

Subjects/Keywords: Statistics; Robust optimization; Machine learning; Mathematical optimization

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APA (6th Edition):

Kang, Y. (2017). Distributionally Robust Optimization and its Applications in Machine Learning. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8WD4C1R

Chicago Manual of Style (16th Edition):

Kang, Yang. “Distributionally Robust Optimization and its Applications in Machine Learning.” 2017. Doctoral Dissertation, Columbia University. Accessed May 11, 2021. https://doi.org/10.7916/D8WD4C1R.

MLA Handbook (7th Edition):

Kang, Yang. “Distributionally Robust Optimization and its Applications in Machine Learning.” 2017. Web. 11 May 2021.

Vancouver:

Kang Y. Distributionally Robust Optimization and its Applications in Machine Learning. [Internet] [Doctoral dissertation]. Columbia University; 2017. [cited 2021 May 11]. Available from: https://doi.org/10.7916/D8WD4C1R.

Council of Science Editors:

Kang Y. Distributionally Robust Optimization and its Applications in Machine Learning. [Doctoral Dissertation]. Columbia University; 2017. Available from: https://doi.org/10.7916/D8WD4C1R


University of Manchester

10. Yang, Xiao. Operational Optimization of Crude Oil Distillation Systems with Limited Information.

Degree: 2020, University of Manchester

 Crude oil distillation is the locomotive of refining and petrochemical industries. Due to massive throughput and energy demand of industrial crude oil distillation systems, even… (more)

Subjects/Keywords: operational optimization; crude oil distillation; real-time optimization; robust optimization

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APA (6th Edition):

Yang, X. (2020). Operational Optimization of Crude Oil Distillation Systems with Limited Information. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:323546

Chicago Manual of Style (16th Edition):

Yang, Xiao. “Operational Optimization of Crude Oil Distillation Systems with Limited Information.” 2020. Doctoral Dissertation, University of Manchester. Accessed May 11, 2021. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:323546.

MLA Handbook (7th Edition):

Yang, Xiao. “Operational Optimization of Crude Oil Distillation Systems with Limited Information.” 2020. Web. 11 May 2021.

Vancouver:

Yang X. Operational Optimization of Crude Oil Distillation Systems with Limited Information. [Internet] [Doctoral dissertation]. University of Manchester; 2020. [cited 2021 May 11]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:323546.

Council of Science Editors:

Yang X. Operational Optimization of Crude Oil Distillation Systems with Limited Information. [Doctoral Dissertation]. University of Manchester; 2020. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:323546

11. Yang, Xiao. Operational optimization of crude oil distillation systems with limited information.

Degree: PhD, 2019, University of Manchester

 Crude oil distillation is the locomotive of refining and petrochemical industries. Due to massive throughput and energy demand of industrial crude oil distillation systems, even… (more)

Subjects/Keywords: robust optimization; real-time optimization; operational optimization; crude oil distillation

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APA (6th Edition):

Yang, X. (2019). Operational optimization of crude oil distillation systems with limited information. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/operational-optimization-of-crude-oil-distillation-systems-with-limited-information(b20546db-e448-4a69-a225-9293554007a4).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.799416

Chicago Manual of Style (16th Edition):

Yang, Xiao. “Operational optimization of crude oil distillation systems with limited information.” 2019. Doctoral Dissertation, University of Manchester. Accessed May 11, 2021. https://www.research.manchester.ac.uk/portal/en/theses/operational-optimization-of-crude-oil-distillation-systems-with-limited-information(b20546db-e448-4a69-a225-9293554007a4).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.799416.

MLA Handbook (7th Edition):

Yang, Xiao. “Operational optimization of crude oil distillation systems with limited information.” 2019. Web. 11 May 2021.

Vancouver:

Yang X. Operational optimization of crude oil distillation systems with limited information. [Internet] [Doctoral dissertation]. University of Manchester; 2019. [cited 2021 May 11]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/operational-optimization-of-crude-oil-distillation-systems-with-limited-information(b20546db-e448-4a69-a225-9293554007a4).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.799416.

Council of Science Editors:

Yang X. Operational optimization of crude oil distillation systems with limited information. [Doctoral Dissertation]. University of Manchester; 2019. Available from: https://www.research.manchester.ac.uk/portal/en/theses/operational-optimization-of-crude-oil-distillation-systems-with-limited-information(b20546db-e448-4a69-a225-9293554007a4).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.799416

12. Espinoza García, Juan Carlos. Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise.

Degree: Docteur es, Sciences de gestion, 2017, Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales

L’objectif de cette thèse est de proposer des solutions efficaces à des problèmes de décision qui ont un impact sur la vie des citoyens, et… (more)

Subjects/Keywords: Optimisation robust; Modèles de choix; Robust optimization; Location problems; Choice models

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APA (6th Edition):

Espinoza García, J. C. (2017). Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise. (Doctoral Dissertation). Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales. Retrieved from http://www.theses.fr/2017ESEC0004

Chicago Manual of Style (16th Edition):

Espinoza García, Juan Carlos. “Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise.” 2017. Doctoral Dissertation, Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales. Accessed May 11, 2021. http://www.theses.fr/2017ESEC0004.

MLA Handbook (7th Edition):

Espinoza García, Juan Carlos. “Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise.” 2017. Web. 11 May 2021.

Vancouver:

Espinoza García JC. Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise. [Internet] [Doctoral dissertation]. Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales; 2017. [cited 2021 May 11]. Available from: http://www.theses.fr/2017ESEC0004.

Council of Science Editors:

Espinoza García JC. Robust optimization for discrete structures and non-linear impact of uncertainty : Gouverner ou être gouverné ? : L'agence en conseil de vote, un acteur en construction dans la gouvernance d'entreprise. [Doctoral Dissertation]. Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales; 2017. Available from: http://www.theses.fr/2017ESEC0004


Mississippi State University

13. Baez-Rivera, Yamilka Isabel. CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP.

Degree: PhD, Electrical and Computer Engineering, 2011, Mississippi State University

 <p class=Basictextdouble-spaced>The next generation of U.S. Navy ships will see the integration of the propulsion and electrical systems as part of the all-electric ship.<span style='mso-spacerun:yes'>… (more)

Subjects/Keywords: optimization; stability; shipboard power systems; robust control

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APA (6th Edition):

Baez-Rivera, Y. I. (2011). CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP. (Doctoral Dissertation). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;

Chicago Manual of Style (16th Edition):

Baez-Rivera, Yamilka Isabel. “CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP.” 2011. Doctoral Dissertation, Mississippi State University. Accessed May 11, 2021. http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;.

MLA Handbook (7th Edition):

Baez-Rivera, Yamilka Isabel. “CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP.” 2011. Web. 11 May 2021.

Vancouver:

Baez-Rivera YI. CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP. [Internet] [Doctoral dissertation]. Mississippi State University; 2011. [cited 2021 May 11]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;.

Council of Science Editors:

Baez-Rivera YI. CONTROL OF MULTIGENERATORS FOR THE ALL-ELECTRIC SHIP. [Doctoral Dissertation]. Mississippi State University; 2011. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-04042011-173542/ ;


University of Houston

14. -5175-3131. Intensity Modulated Proton Therapy Optimization Under Uncertainty: Field Misalignment and Internal Organ Motion.

Degree: PhD, Industrial Engineering, 2016, University of Houston

 Intensity modulated proton therapy (IMPT) is one of the most advanced forms of radiation therapy, which can deliver a highly conformal dose to the tumor… (more)

Subjects/Keywords: Intensity Modulated Proton Therapy; Robust optimization

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APA (6th Edition):

-5175-3131. (2016). Intensity Modulated Proton Therapy Optimization Under Uncertainty: Field Misalignment and Internal Organ Motion. (Doctoral Dissertation). University of Houston. Retrieved from http://hdl.handle.net/10657/5441

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

Chicago Manual of Style (16th Edition):

-5175-3131. “Intensity Modulated Proton Therapy Optimization Under Uncertainty: Field Misalignment and Internal Organ Motion.” 2016. Doctoral Dissertation, University of Houston. Accessed May 11, 2021. http://hdl.handle.net/10657/5441.

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

MLA Handbook (7th Edition):

-5175-3131. “Intensity Modulated Proton Therapy Optimization Under Uncertainty: Field Misalignment and Internal Organ Motion.” 2016. Web. 11 May 2021.

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

Vancouver:

-5175-3131. Intensity Modulated Proton Therapy Optimization Under Uncertainty: Field Misalignment and Internal Organ Motion. [Internet] [Doctoral dissertation]. University of Houston; 2016. [cited 2021 May 11]. Available from: http://hdl.handle.net/10657/5441.

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

Council of Science Editors:

-5175-3131. Intensity Modulated Proton Therapy Optimization Under Uncertainty: Field Misalignment and Internal Organ Motion. [Doctoral Dissertation]. University of Houston; 2016. Available from: http://hdl.handle.net/10657/5441

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


Columbia University

15. Qu, Qing. Nonconvex Recovery of Low-complexity Models.

Degree: 2018, Columbia University

 Today we are living in the era of big data, there is a pressing need for efficient, scalable and robust optimization methods to analyze the… (more)

Subjects/Keywords: Electrical engineering; Nonconvex programming; Robust optimization

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APA (6th Edition):

Qu, Q. (2018). Nonconvex Recovery of Low-complexity Models. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8TJ04K8

Chicago Manual of Style (16th Edition):

Qu, Qing. “Nonconvex Recovery of Low-complexity Models.” 2018. Doctoral Dissertation, Columbia University. Accessed May 11, 2021. https://doi.org/10.7916/D8TJ04K8.

MLA Handbook (7th Edition):

Qu, Qing. “Nonconvex Recovery of Low-complexity Models.” 2018. Web. 11 May 2021.

Vancouver:

Qu Q. Nonconvex Recovery of Low-complexity Models. [Internet] [Doctoral dissertation]. Columbia University; 2018. [cited 2021 May 11]. Available from: https://doi.org/10.7916/D8TJ04K8.

Council of Science Editors:

Qu Q. Nonconvex Recovery of Low-complexity Models. [Doctoral Dissertation]. Columbia University; 2018. Available from: https://doi.org/10.7916/D8TJ04K8


Hong Kong University of Science and Technology

16. Sun, Ying. Majorization-minimization algorithm and its applications in robust covariance matrix estimation.

Degree: 2016, Hong Kong University of Science and Technology

 Covariance estimation has been a fundamental and long existing problem, closely related to various fields including multi-antenna communication systems, social networks, bioinformatics, and financial engineering.… (more)

Subjects/Keywords: Analysis of covariance ; Estimation theory ; Robust optimization

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APA (6th Edition):

Sun, Y. (2016). Majorization-minimization algorithm and its applications in robust covariance matrix estimation. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-86941 ; https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html

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):

Sun, Ying. “Majorization-minimization algorithm and its applications in robust covariance matrix estimation.” 2016. Thesis, Hong Kong University of Science and Technology. Accessed May 11, 2021. http://repository.ust.hk/ir/Record/1783.1-86941 ; https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Sun, Ying. “Majorization-minimization algorithm and its applications in robust covariance matrix estimation.” 2016. Web. 11 May 2021.

Vancouver:

Sun Y. Majorization-minimization algorithm and its applications in robust covariance matrix estimation. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2016. [cited 2021 May 11]. Available from: http://repository.ust.hk/ir/Record/1783.1-86941 ; https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html.

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

Council of Science Editors:

Sun Y. Majorization-minimization algorithm and its applications in robust covariance matrix estimation. [Thesis]. Hong Kong University of Science and Technology; 2016. Available from: http://repository.ust.hk/ir/Record/1783.1-86941 ; https://doi.org/10.14711/thesis-b1626265 ; http://repository.ust.hk/ir/bitstream/1783.1-86941/1/th_redirect.html

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


Georgia Tech

17. Lorca Galvez, Alvaro Hugo. Robust optimization for renewable energy integration in power system operations.

Degree: PhD, Industrial and Systems Engineering, 2016, Georgia Tech

Optimization provides critical support for the operation of electric power systems. As power systems evolve, enhanced operational methodologies are required, and innovative optimization models have… (more)

Subjects/Keywords: Robust optimization; Power system operations; Renewable energy

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APA (6th Edition):

Lorca Galvez, A. H. (2016). Robust optimization for renewable energy integration in power system operations. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55653

Chicago Manual of Style (16th Edition):

Lorca Galvez, Alvaro Hugo. “Robust optimization for renewable energy integration in power system operations.” 2016. Doctoral Dissertation, Georgia Tech. Accessed May 11, 2021. http://hdl.handle.net/1853/55653.

MLA Handbook (7th Edition):

Lorca Galvez, Alvaro Hugo. “Robust optimization for renewable energy integration in power system operations.” 2016. Web. 11 May 2021.

Vancouver:

Lorca Galvez AH. Robust optimization for renewable energy integration in power system operations. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2021 May 11]. Available from: http://hdl.handle.net/1853/55653.

Council of Science Editors:

Lorca Galvez AH. Robust optimization for renewable energy integration in power system operations. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55653


Lehigh University

18. Dong, Yang. Robust Performance Attribution Analysis in Investment Management.

Degree: PhD, Information and Systems Engineering, 2014, Lehigh University

 This dissertation investigates robust optimization models for performance attribution analysis in investment management. Specifically, an investment manager seeks to evaluate the performance of fund managers… (more)

Subjects/Keywords: Portfolio management; Robust optimization; Uncertainty; Engineering

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APA (6th Edition):

Dong, Y. (2014). Robust Performance Attribution Analysis in Investment Management. (Doctoral Dissertation). Lehigh University. Retrieved from https://preserve.lehigh.edu/etd/1474

Chicago Manual of Style (16th Edition):

Dong, Yang. “Robust Performance Attribution Analysis in Investment Management.” 2014. Doctoral Dissertation, Lehigh University. Accessed May 11, 2021. https://preserve.lehigh.edu/etd/1474.

MLA Handbook (7th Edition):

Dong, Yang. “Robust Performance Attribution Analysis in Investment Management.” 2014. Web. 11 May 2021.

Vancouver:

Dong Y. Robust Performance Attribution Analysis in Investment Management. [Internet] [Doctoral dissertation]. Lehigh University; 2014. [cited 2021 May 11]. Available from: https://preserve.lehigh.edu/etd/1474.

Council of Science Editors:

Dong Y. Robust Performance Attribution Analysis in Investment Management. [Doctoral Dissertation]. Lehigh University; 2014. Available from: https://preserve.lehigh.edu/etd/1474


University of Pennsylvania

19. Fazlyab, Mahyar. Control Theoretic Methods In Analysis And Design Of Optimization Algorithms.

Degree: 2018, University of Pennsylvania

 Recently, there has been a surge of interest in incorporating tools from dynamical systems and control theory to analyze and design iterative optimization algorithms. This… (more)

Subjects/Keywords: Iterative Algorithms; Numerical Optimization; Robust Control; Engineering

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APA (6th Edition):

Fazlyab, M. (2018). Control Theoretic Methods In Analysis And Design Of Optimization Algorithms. (Thesis). University of Pennsylvania. Retrieved from https://repository.upenn.edu/edissertations/3066

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):

Fazlyab, Mahyar. “Control Theoretic Methods In Analysis And Design Of Optimization Algorithms.” 2018. Thesis, University of Pennsylvania. Accessed May 11, 2021. https://repository.upenn.edu/edissertations/3066.

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

MLA Handbook (7th Edition):

Fazlyab, Mahyar. “Control Theoretic Methods In Analysis And Design Of Optimization Algorithms.” 2018. Web. 11 May 2021.

Vancouver:

Fazlyab M. Control Theoretic Methods In Analysis And Design Of Optimization Algorithms. [Internet] [Thesis]. University of Pennsylvania; 2018. [cited 2021 May 11]. Available from: https://repository.upenn.edu/edissertations/3066.

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

Council of Science Editors:

Fazlyab M. Control Theoretic Methods In Analysis And Design Of Optimization Algorithms. [Thesis]. University of Pennsylvania; 2018. Available from: https://repository.upenn.edu/edissertations/3066

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


University of Oregon

20. Torkamani, MohamadAli. Robust Large Margin Approaches for Machine Learning in Adversarial Settings.

Degree: PhD, Department of Computer and Information Science, 2016, University of Oregon

 Machine learning algorithms are invented to learn from data and to use data to perform predictions and analyses. Many agencies are now using machine learning… (more)

Subjects/Keywords: Adversarial machine learning; Convex optimization; Customized regularization; Dropout; Robust machine learning; Robust optimization

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

APA (6th Edition):

Torkamani, M. (2016). Robust Large Margin Approaches for Machine Learning in Adversarial Settings. (Doctoral Dissertation). University of Oregon. Retrieved from http://hdl.handle.net/1794/20677

Chicago Manual of Style (16th Edition):

Torkamani, MohamadAli. “Robust Large Margin Approaches for Machine Learning in Adversarial Settings.” 2016. Doctoral Dissertation, University of Oregon. Accessed May 11, 2021. http://hdl.handle.net/1794/20677.

MLA Handbook (7th Edition):

Torkamani, MohamadAli. “Robust Large Margin Approaches for Machine Learning in Adversarial Settings.” 2016. Web. 11 May 2021.

Vancouver:

Torkamani M. Robust Large Margin Approaches for Machine Learning in Adversarial Settings. [Internet] [Doctoral dissertation]. University of Oregon; 2016. [cited 2021 May 11]. Available from: http://hdl.handle.net/1794/20677.

Council of Science Editors:

Torkamani M. Robust Large Margin Approaches for Machine Learning in Adversarial Settings. [Doctoral Dissertation]. University of Oregon; 2016. Available from: http://hdl.handle.net/1794/20677


Cornell University

21. Ning, Chao. DATA-DRIVEN OPTIMIZATION UNDER UNCERTAINTY IN THE ERA OF BIG DATA AND DEEP LEARNING: GENERAL FRAMEWORKS, ALGORITHMS, AND APPLICATIONS.

Degree: PhD, Chemical Engineering, 2020, Cornell University

 This dissertation deals with the development of fundamental data-driven optimization under uncertainty, including its modeling frameworks, solution algorithms, and a wide variety of applications. Specifically,… (more)

Subjects/Keywords: Data-driven optimization; Machine learning; Model predictive control; Optimization under uncertainty; Robust optimization; Stochastic optimization

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

APA (6th Edition):

Ning, C. (2020). DATA-DRIVEN OPTIMIZATION UNDER UNCERTAINTY IN THE ERA OF BIG DATA AND DEEP LEARNING: GENERAL FRAMEWORKS, ALGORITHMS, AND APPLICATIONS. (Doctoral Dissertation). Cornell University. Retrieved from http://hdl.handle.net/1813/102966

Chicago Manual of Style (16th Edition):

Ning, Chao. “DATA-DRIVEN OPTIMIZATION UNDER UNCERTAINTY IN THE ERA OF BIG DATA AND DEEP LEARNING: GENERAL FRAMEWORKS, ALGORITHMS, AND APPLICATIONS.” 2020. Doctoral Dissertation, Cornell University. Accessed May 11, 2021. http://hdl.handle.net/1813/102966.

MLA Handbook (7th Edition):

Ning, Chao. “DATA-DRIVEN OPTIMIZATION UNDER UNCERTAINTY IN THE ERA OF BIG DATA AND DEEP LEARNING: GENERAL FRAMEWORKS, ALGORITHMS, AND APPLICATIONS.” 2020. Web. 11 May 2021.

Vancouver:

Ning C. DATA-DRIVEN OPTIMIZATION UNDER UNCERTAINTY IN THE ERA OF BIG DATA AND DEEP LEARNING: GENERAL FRAMEWORKS, ALGORITHMS, AND APPLICATIONS. [Internet] [Doctoral dissertation]. Cornell University; 2020. [cited 2021 May 11]. Available from: http://hdl.handle.net/1813/102966.

Council of Science Editors:

Ning C. DATA-DRIVEN OPTIMIZATION UNDER UNCERTAINTY IN THE ERA OF BIG DATA AND DEEP LEARNING: GENERAL FRAMEWORKS, ALGORITHMS, AND APPLICATIONS. [Doctoral Dissertation]. Cornell University; 2020. Available from: http://hdl.handle.net/1813/102966

22. Kurtz, Jannis. Min-max-min robust combinatorial optimization.

Degree: 2016, Technische Universität Dortmund

 In this thesis we introduce a robust optimization approach which is based on a binary min-max-min problem. The so called Min-max-min Robust Optimization extends the… (more)

Subjects/Keywords: Min-max-min; Robust optimization; Combinatorial optimization; 510; Robuste Optimierung; Komplexität

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

APA (6th Edition):

Kurtz, J. (2016). Min-max-min robust combinatorial optimization. (Doctoral Dissertation). Technische Universität Dortmund. Retrieved from http://dx.doi.org/10.17877/DE290R-17366

Chicago Manual of Style (16th Edition):

Kurtz, Jannis. “Min-max-min robust combinatorial optimization.” 2016. Doctoral Dissertation, Technische Universität Dortmund. Accessed May 11, 2021. http://dx.doi.org/10.17877/DE290R-17366.

MLA Handbook (7th Edition):

Kurtz, Jannis. “Min-max-min robust combinatorial optimization.” 2016. Web. 11 May 2021.

Vancouver:

Kurtz J. Min-max-min robust combinatorial optimization. [Internet] [Doctoral dissertation]. Technische Universität Dortmund; 2016. [cited 2021 May 11]. Available from: http://dx.doi.org/10.17877/DE290R-17366.

Council of Science Editors:

Kurtz J. Min-max-min robust combinatorial optimization. [Doctoral Dissertation]. Technische Universität Dortmund; 2016. Available from: http://dx.doi.org/10.17877/DE290R-17366

23. Bindewald, Viktor. Bulk-robust assignment problems: hardness, approximability and algorithms.

Degree: 2017, Technische Universität Dortmund

 Diese Dissertation behandelt robuste Zuordnungsprobleme mit dem Schwerpunkt auf deren komlexitätstheoretischen Eigenschaften. Zuordnungsprobleme sind gut untersuchte kombinatorische Optimierungsprobleme mit vielen praktischen Anwendungen, z. B. in… (more)

Subjects/Keywords: Combinatorial optimization; Robust optimization; Matchings; 510; Zuordnungsproblem; Robuste Optimierung

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APA (6th Edition):

Bindewald, V. (2017). Bulk-robust assignment problems: hardness, approximability and algorithms. (Doctoral Dissertation). Technische Universität Dortmund. Retrieved from http://dx.doi.org/10.17877/DE290R-19108

Chicago Manual of Style (16th Edition):

Bindewald, Viktor. “Bulk-robust assignment problems: hardness, approximability and algorithms.” 2017. Doctoral Dissertation, Technische Universität Dortmund. Accessed May 11, 2021. http://dx.doi.org/10.17877/DE290R-19108.

MLA Handbook (7th Edition):

Bindewald, Viktor. “Bulk-robust assignment problems: hardness, approximability and algorithms.” 2017. Web. 11 May 2021.

Vancouver:

Bindewald V. Bulk-robust assignment problems: hardness, approximability and algorithms. [Internet] [Doctoral dissertation]. Technische Universität Dortmund; 2017. [cited 2021 May 11]. Available from: http://dx.doi.org/10.17877/DE290R-19108.

Council of Science Editors:

Bindewald V. Bulk-robust assignment problems: hardness, approximability and algorithms. [Doctoral Dissertation]. Technische Universität Dortmund; 2017. Available from: http://dx.doi.org/10.17877/DE290R-19108


Columbia University

24. Lu, Brian Yin. Essays on Approximation Algorithms for Robust Linear Optimization Problems.

Degree: 2016, Columbia University

 Solving optimization problems under uncertainty has been an important topic since the appearance of mathematical optimization in the mid 19th century. George Dantzig’s 1955 paper,… (more)

Subjects/Keywords: Mathematical optimization; Uncertainty (Information theory); Robust optimization; Approximation algorithms; Operations research

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

APA (6th Edition):

Lu, B. Y. (2016). Essays on Approximation Algorithms for Robust Linear Optimization Problems. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8ZG6SGM

Chicago Manual of Style (16th Edition):

Lu, Brian Yin. “Essays on Approximation Algorithms for Robust Linear Optimization Problems.” 2016. Doctoral Dissertation, Columbia University. Accessed May 11, 2021. https://doi.org/10.7916/D8ZG6SGM.

MLA Handbook (7th Edition):

Lu, Brian Yin. “Essays on Approximation Algorithms for Robust Linear Optimization Problems.” 2016. Web. 11 May 2021.

Vancouver:

Lu BY. Essays on Approximation Algorithms for Robust Linear Optimization Problems. [Internet] [Doctoral dissertation]. Columbia University; 2016. [cited 2021 May 11]. Available from: https://doi.org/10.7916/D8ZG6SGM.

Council of Science Editors:

Lu BY. Essays on Approximation Algorithms for Robust Linear Optimization Problems. [Doctoral Dissertation]. Columbia University; 2016. Available from: https://doi.org/10.7916/D8ZG6SGM


University of Illinois – Urbana-Champaign

25. Anderson, Jesse Cole. Robust design optimization with dynamic constraints using numerical continuation.

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

 This thesis develops a framework for performing robust design optimization of objective functions constrained by differential, algebraic, and integral constraints. A successive parameter continuation method… (more)

Subjects/Keywords: continuation; optimization; robust optimization; polynomial chaos expansion; Duffing oscillator

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APA (6th Edition):

Anderson, J. C. (2019). Robust design optimization with dynamic constraints using numerical continuation. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/104728

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):

Anderson, Jesse Cole. “Robust design optimization with dynamic constraints using numerical continuation.” 2019. Thesis, University of Illinois – Urbana-Champaign. Accessed May 11, 2021. http://hdl.handle.net/2142/104728.

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

MLA Handbook (7th Edition):

Anderson, Jesse Cole. “Robust design optimization with dynamic constraints using numerical continuation.” 2019. Web. 11 May 2021.

Vancouver:

Anderson JC. Robust design optimization with dynamic constraints using numerical continuation. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2019. [cited 2021 May 11]. Available from: http://hdl.handle.net/2142/104728.

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

Council of Science Editors:

Anderson JC. Robust design optimization with dynamic constraints using numerical continuation. [Thesis]. University of Illinois – Urbana-Champaign; 2019. Available from: http://hdl.handle.net/2142/104728

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


University of New South Wales

26. Asafuddoula, Md. Development of algorithms to solve different key challenges facing design optimization.

Degree: Engineering & Information Technology, 2014, University of New South Wales

Optimization methods play an indispensable role in today’s competitive environmentand there are plenty of practical examples where such methods have been used toidentify better performing… (more)

Subjects/Keywords: Robust design optimization; Constraint handling; Many objective optimization

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APA (6th Edition):

Asafuddoula, M. (2014). Development of algorithms to solve different key challenges facing design optimization. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Asafuddoula, Md. “Development of algorithms to solve different key challenges facing design optimization.” 2014. Doctoral Dissertation, University of New South Wales. Accessed May 11, 2021. http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true.

MLA Handbook (7th Edition):

Asafuddoula, Md. “Development of algorithms to solve different key challenges facing design optimization.” 2014. Web. 11 May 2021.

Vancouver:

Asafuddoula M. Development of algorithms to solve different key challenges facing design optimization. [Internet] [Doctoral dissertation]. University of New South Wales; 2014. [cited 2021 May 11]. Available from: http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true.

Council of Science Editors:

Asafuddoula M. Development of algorithms to solve different key challenges facing design optimization. [Doctoral Dissertation]. University of New South Wales; 2014. Available from: http://handle.unsw.edu.au/1959.4/53458 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12153/SOURCE02?view=true


Princeton University

27. Matthews, Logan Ryan. Advancing Robust Optimization for Process Systems Engineering Applications .

Degree: PhD, 2018, Princeton University

Robust optimization is a popular method for incorporating parameter uncertainty into optimization models. Whether parameters represent the price of a feedstock or product, the operability… (more)

Subjects/Keywords: Global Optimization; Optimization Under Uncertainty; Process Synthesis; Resilient Network Design; Robust Optimization

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APA (6th Edition):

Matthews, L. R. (2018). Advancing Robust Optimization for Process Systems Engineering Applications . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j

Chicago Manual of Style (16th Edition):

Matthews, Logan Ryan. “Advancing Robust Optimization for Process Systems Engineering Applications .” 2018. Doctoral Dissertation, Princeton University. Accessed May 11, 2021. http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j.

MLA Handbook (7th Edition):

Matthews, Logan Ryan. “Advancing Robust Optimization for Process Systems Engineering Applications .” 2018. Web. 11 May 2021.

Vancouver:

Matthews LR. Advancing Robust Optimization for Process Systems Engineering Applications . [Internet] [Doctoral dissertation]. Princeton University; 2018. [cited 2021 May 11]. Available from: http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j.

Council of Science Editors:

Matthews LR. Advancing Robust Optimization for Process Systems Engineering Applications . [Doctoral Dissertation]. Princeton University; 2018. Available from: http://arks.princeton.edu/ark:/88435/dsp01hh63sz60j


Loughborough University

28. Rossetti, Gaia. Mathematical optimization techniques for cognitive radar networks.

Degree: Mechanical, Electrical and Manufacturing Engineering, 2018, Loughborough University

 This thesis discusses mathematical optimization techniques for waveform design in cognitive radars. These techniques have been designed with an increasing level of sophistication, starting from… (more)

Subjects/Keywords: Mechanical Engineering not elsewhere classified; Waveform optimization; Convex optimization; Robust optimization; Cognitive radars

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APA (6th Edition):

Rossetti, G. (2018). Mathematical optimization techniques for cognitive radar networks. (Thesis). Loughborough University. Retrieved from http://hdl.handle.net/2134/33419

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):

Rossetti, Gaia. “Mathematical optimization techniques for cognitive radar networks.” 2018. Thesis, Loughborough University. Accessed May 11, 2021. http://hdl.handle.net/2134/33419.

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

MLA Handbook (7th Edition):

Rossetti, Gaia. “Mathematical optimization techniques for cognitive radar networks.” 2018. Web. 11 May 2021.

Vancouver:

Rossetti G. Mathematical optimization techniques for cognitive radar networks. [Internet] [Thesis]. Loughborough University; 2018. [cited 2021 May 11]. Available from: http://hdl.handle.net/2134/33419.

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

Council of Science Editors:

Rossetti G. Mathematical optimization techniques for cognitive radar networks. [Thesis]. Loughborough University; 2018. Available from: http://hdl.handle.net/2134/33419

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


Penn State University

29. Bekiroglu, Korkut. From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments.

Degree: 2015, Penn State University

 Behavioral and social scientists have demonstrated the advantages of the adaptive treatments, which usually provide better results than the fixed treatment (all patients get same… (more)

Subjects/Keywords: Adaptive Intervention; Robust Treatment Design; System Identification; Atomic Norm; min-max Structured Robust Optimization

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APA (6th Edition):

Bekiroglu, K. (2015). From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/26227

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):

Bekiroglu, Korkut. “From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments.” 2015. Thesis, Penn State University. Accessed May 11, 2021. https://submit-etda.libraries.psu.edu/catalog/26227.

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

MLA Handbook (7th Edition):

Bekiroglu, Korkut. “From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments.” 2015. Web. 11 May 2021.

Vancouver:

Bekiroglu K. From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments. [Internet] [Thesis]. Penn State University; 2015. [cited 2021 May 11]. Available from: https://submit-etda.libraries.psu.edu/catalog/26227.

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

Council of Science Editors:

Bekiroglu K. From Data to Interventions: Using System Identification and Robust Control Algorithms to Design Effective Treatments. [Thesis]. Penn State University; 2015. Available from: https://submit-etda.libraries.psu.edu/catalog/26227

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


University of Manchester

30. Diaz Leiva, Juan Esteban. Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems.

Degree: 2016, University of Manchester

This doctoral thesis investigates the application of simulation-based optimization (SBO) as an alternative to conventional optimization techniques when the inherent uncertainty and complex features of… (more)

Subjects/Keywords: Combinatorial optimization; Genetic algorithms; Matheuristics; Meta-heuristics; Multi-objective optimization; Production planning; Robust optimization; Simulation-based optimization; Uncertainty modelling

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APA (6th Edition):

Diaz Leiva, J. E. (2016). Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199

Chicago Manual of Style (16th Edition):

Diaz Leiva, Juan Esteban. “Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems.” 2016. Doctoral Dissertation, University of Manchester. Accessed May 11, 2021. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199.

MLA Handbook (7th Edition):

Diaz Leiva, Juan Esteban. “Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems.” 2016. Web. 11 May 2021.

Vancouver:

Diaz Leiva JE. Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems. [Internet] [Doctoral dissertation]. University of Manchester; 2016. [cited 2021 May 11]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199.

Council of Science Editors:

Diaz Leiva JE. Simulation-Based Optimization for Production Planning: Integrating Meta-Heuristics, Simulation and Exact Techniques to Address the Uncertainty and Complexity of Manufacturing Systems. [Doctoral Dissertation]. University of Manchester; 2016. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:301199

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