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You searched for subject:(Operations Research Robust Optimization). Showing records 1 – 30 of 67666 total matches.

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University of Southern California

1. Ye, Wei. Models and algorithms for energy efficient wireless sensor networks.

Degree: PhD, Industrial & Systems Engineering, 2009, University of Southern California

 Wireless Sensor Networks (WSNs) is an area of active research in industry and academia. WSNs can be used in a wide array of applications such… (more)

Subjects/Keywords: wireless sensor networks; robust optimization; nonlinear optimization; operations research

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APA (6th Edition):

Ye, W. (2009). Models and algorithms for energy efficient wireless sensor networks. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151

Chicago Manual of Style (16th Edition):

Ye, Wei. “Models and algorithms for energy efficient wireless sensor networks.” 2009. Doctoral Dissertation, University of Southern California. Accessed January 21, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151.

MLA Handbook (7th Edition):

Ye, Wei. “Models and algorithms for energy efficient wireless sensor networks.” 2009. Web. 21 Jan 2020.

Vancouver:

Ye W. Models and algorithms for energy efficient wireless sensor networks. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2020 Jan 21]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151.

Council of Science Editors:

Ye W. Models and algorithms for energy efficient wireless sensor networks. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/483963/rec/4151


Columbia University

2. 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 (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 January 21, 2020. https://doi.org/10.7916/D8ZG6SGM.

MLA Handbook (7th Edition):

Lu, Brian Yin. “Essays on Approximation Algorithms for Robust Linear Optimization Problems.” 2016. Web. 21 Jan 2020.

Vancouver:

Lu BY. Essays on Approximation Algorithms for Robust Linear Optimization Problems. [Internet] [Doctoral dissertation]. Columbia University; 2016. [cited 2020 Jan 21]. 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 Vienna

3. Steurer, Fabian. Robust Optimization.

Degree: 2017, University of Vienna

Diese Masterarbeit behandelt das Thema Robuste Optimierung. Dies sind Op- timierungsprobleme die von Unsicherheiten in den Daten beeinflusst werden, wie dies auch häufig in praktischen… (more)

Subjects/Keywords: 31.80 Angewandte Mathematik; Robuste Optimierung; Operations Research / Robust Optimization

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APA (6th Edition):

Steurer, F. (2017). Robust Optimization. (Thesis). University of Vienna. Retrieved from http://othes.univie.ac.at/48571/

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):

Steurer, Fabian. “Robust Optimization.” 2017. Thesis, University of Vienna. Accessed January 21, 2020. http://othes.univie.ac.at/48571/.

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

MLA Handbook (7th Edition):

Steurer, Fabian. “Robust Optimization.” 2017. Web. 21 Jan 2020.

Vancouver:

Steurer F. Robust Optimization. [Internet] [Thesis]. University of Vienna; 2017. [cited 2020 Jan 21]. Available from: http://othes.univie.ac.at/48571/.

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

Council of Science Editors:

Steurer F. Robust Optimization. [Thesis]. University of Vienna; 2017. Available from: http://othes.univie.ac.at/48571/

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


Cornell University

4. Dong, James. ROBUST MULTI-PRODUCT NEWSVENDOR PROBLEM UNDER A GLOBAL BUDGET OF UNCERTAINTY .

Degree: 2018, Cornell University

 We consider a single-location, single-period stock allocation problem (newsvendor-like problem) with n items in which demand rates, holding costs, and backorder costs vary across all… (more)

Subjects/Keywords: Operations research; Inventory Theory; Newsvendor Problem; robust optimization

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APA (6th Edition):

Dong, J. (2018). ROBUST MULTI-PRODUCT NEWSVENDOR PROBLEM UNDER A GLOBAL BUDGET OF UNCERTAINTY . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/59287

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):

Dong, James. “ROBUST MULTI-PRODUCT NEWSVENDOR PROBLEM UNDER A GLOBAL BUDGET OF UNCERTAINTY .” 2018. Thesis, Cornell University. Accessed January 21, 2020. http://hdl.handle.net/1813/59287.

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

MLA Handbook (7th Edition):

Dong, James. “ROBUST MULTI-PRODUCT NEWSVENDOR PROBLEM UNDER A GLOBAL BUDGET OF UNCERTAINTY .” 2018. Web. 21 Jan 2020.

Vancouver:

Dong J. ROBUST MULTI-PRODUCT NEWSVENDOR PROBLEM UNDER A GLOBAL BUDGET OF UNCERTAINTY . [Internet] [Thesis]. Cornell University; 2018. [cited 2020 Jan 21]. Available from: http://hdl.handle.net/1813/59287.

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

Council of Science Editors:

Dong J. ROBUST MULTI-PRODUCT NEWSVENDOR PROBLEM UNDER A GLOBAL BUDGET OF UNCERTAINTY . [Thesis]. Cornell University; 2018. Available from: http://hdl.handle.net/1813/59287

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


University of Oklahoma

5. Almaraj, Ismail. An Integrated Multi-Echelon Multi-Objective Programming Robust Closed-Loop Supply Chain Under Dynamic Uncertainty Sets and Imperfect Quality Production.

Degree: PhD, 2019, University of Oklahoma

 Modeling robust closed- loop supply chain under multiple uncertainties and multiple criteria where imperfect quality production is incorporated is a new research trend in this… (more)

Subjects/Keywords: Operations Research; Robust Optimization; Production Systems and Supply Chain Management; Optimization under Uncertainty

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APA (6th Edition):

Almaraj, I. (2019). An Integrated Multi-Echelon Multi-Objective Programming Robust Closed-Loop Supply Chain Under Dynamic Uncertainty Sets and Imperfect Quality Production. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/319573

Chicago Manual of Style (16th Edition):

Almaraj, Ismail. “An Integrated Multi-Echelon Multi-Objective Programming Robust Closed-Loop Supply Chain Under Dynamic Uncertainty Sets and Imperfect Quality Production.” 2019. Doctoral Dissertation, University of Oklahoma. Accessed January 21, 2020. http://hdl.handle.net/11244/319573.

MLA Handbook (7th Edition):

Almaraj, Ismail. “An Integrated Multi-Echelon Multi-Objective Programming Robust Closed-Loop Supply Chain Under Dynamic Uncertainty Sets and Imperfect Quality Production.” 2019. Web. 21 Jan 2020.

Vancouver:

Almaraj I. An Integrated Multi-Echelon Multi-Objective Programming Robust Closed-Loop Supply Chain Under Dynamic Uncertainty Sets and Imperfect Quality Production. [Internet] [Doctoral dissertation]. University of Oklahoma; 2019. [cited 2020 Jan 21]. Available from: http://hdl.handle.net/11244/319573.

Council of Science Editors:

Almaraj I. An Integrated Multi-Echelon Multi-Objective Programming Robust Closed-Loop Supply Chain Under Dynamic Uncertainty Sets and Imperfect Quality Production. [Doctoral Dissertation]. University of Oklahoma; 2019. Available from: http://hdl.handle.net/11244/319573


University of Windsor

6. Lalmazloumian, Morteza. Robust Optimization Framework to Operating Room Planning and Scheduling in Stochastic Environment.

Degree: PhD, Mechanical, Automotive, and Materials Engineering, 2017, University of Windsor

 Arrangement of surgical activities can be classified as a three-level process that directly impacts the overall performance of a healthcare system. The goal of this… (more)

Subjects/Keywords: Operating Room; Operations Research; Planning and Scheduling; Robust Optimization; Stochastic Optimization; Uncertainty

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APA (6th Edition):

Lalmazloumian, M. (2017). Robust Optimization Framework to Operating Room Planning and Scheduling in Stochastic Environment. (Doctoral Dissertation). University of Windsor. Retrieved from https://scholar.uwindsor.ca/etd/5994

Chicago Manual of Style (16th Edition):

Lalmazloumian, Morteza. “Robust Optimization Framework to Operating Room Planning and Scheduling in Stochastic Environment.” 2017. Doctoral Dissertation, University of Windsor. Accessed January 21, 2020. https://scholar.uwindsor.ca/etd/5994.

MLA Handbook (7th Edition):

Lalmazloumian, Morteza. “Robust Optimization Framework to Operating Room Planning and Scheduling in Stochastic Environment.” 2017. Web. 21 Jan 2020.

Vancouver:

Lalmazloumian M. Robust Optimization Framework to Operating Room Planning and Scheduling in Stochastic Environment. [Internet] [Doctoral dissertation]. University of Windsor; 2017. [cited 2020 Jan 21]. Available from: https://scholar.uwindsor.ca/etd/5994.

Council of Science Editors:

Lalmazloumian M. Robust Optimization Framework to Operating Room Planning and Scheduling in Stochastic Environment. [Doctoral Dissertation]. University of Windsor; 2017. Available from: https://scholar.uwindsor.ca/etd/5994


University of Iowa

7. Xu, Guanglin. Optimization under uncertainty: conic programming representations, relaxations, and approximations.

Degree: PhD, Business Administration, 2017, University of Iowa

  In practice, the presence of uncertain parameters in optimization problems introduces new challenges in modeling and solvability to operations research. There are three main… (more)

Subjects/Keywords: Conic programming; Copositive programming; Operations research; Robust optimization; Semidefinite programming; Stochastic optimization; Business Administration, Management, and Operations

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APA (6th Edition):

Xu, G. (2017). Optimization under uncertainty: conic programming representations, relaxations, and approximations. (Doctoral Dissertation). University of Iowa. Retrieved from https://ir.uiowa.edu/etd/5881

Chicago Manual of Style (16th Edition):

Xu, Guanglin. “Optimization under uncertainty: conic programming representations, relaxations, and approximations.” 2017. Doctoral Dissertation, University of Iowa. Accessed January 21, 2020. https://ir.uiowa.edu/etd/5881.

MLA Handbook (7th Edition):

Xu, Guanglin. “Optimization under uncertainty: conic programming representations, relaxations, and approximations.” 2017. Web. 21 Jan 2020.

Vancouver:

Xu G. Optimization under uncertainty: conic programming representations, relaxations, and approximations. [Internet] [Doctoral dissertation]. University of Iowa; 2017. [cited 2020 Jan 21]. Available from: https://ir.uiowa.edu/etd/5881.

Council of Science Editors:

Xu G. Optimization under uncertainty: conic programming representations, relaxations, and approximations. [Doctoral Dissertation]. University of Iowa; 2017. Available from: https://ir.uiowa.edu/etd/5881


Lehigh University

8. Xiao, Tengjiao. Robust Healthcare Financing Systems.

Degree: PhD, Industrial Engineering, 2015, Lehigh University

 This dissertation provides robust, quantitative models in healthcare finance to aid decision-makers with rigorous, analytical tools that capture high complexity and high uncertainty of problem.… (more)

Subjects/Keywords: Healthcare Finance; Robust Optimization; Engineering; Industrial Engineering; Operations Research, Systems Engineering and Industrial Engineering

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APA (6th Edition):

Xiao, T. (2015). Robust Healthcare Financing Systems. (Doctoral Dissertation). Lehigh University. Retrieved from https://preserve.lehigh.edu/etd/2884

Chicago Manual of Style (16th Edition):

Xiao, Tengjiao. “Robust Healthcare Financing Systems.” 2015. Doctoral Dissertation, Lehigh University. Accessed January 21, 2020. https://preserve.lehigh.edu/etd/2884.

MLA Handbook (7th Edition):

Xiao, Tengjiao. “Robust Healthcare Financing Systems.” 2015. Web. 21 Jan 2020.

Vancouver:

Xiao T. Robust Healthcare Financing Systems. [Internet] [Doctoral dissertation]. Lehigh University; 2015. [cited 2020 Jan 21]. Available from: https://preserve.lehigh.edu/etd/2884.

Council of Science Editors:

Xiao T. Robust Healthcare Financing Systems. [Doctoral Dissertation]. Lehigh University; 2015. Available from: https://preserve.lehigh.edu/etd/2884


University of Washington

9. Sinha, Saumya. Robust dynamic optimization: theory and applications.

Degree: PhD, 2018, University of Washington

 Many applications in decision-making use a dynamic optimization framework to model a system evolving uncertainly in discrete time, and an agent who chooses actions/controls from… (more)

Subjects/Keywords: dynamic programming; Markov decision processes; robust optimization; Operations research; Applied mathematics; Applied mathematics

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APA (6th Edition):

Sinha, S. (2018). Robust dynamic optimization: theory and applications. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/42949

Chicago Manual of Style (16th Edition):

Sinha, Saumya. “Robust dynamic optimization: theory and applications.” 2018. Doctoral Dissertation, University of Washington. Accessed January 21, 2020. http://hdl.handle.net/1773/42949.

MLA Handbook (7th Edition):

Sinha, Saumya. “Robust dynamic optimization: theory and applications.” 2018. Web. 21 Jan 2020.

Vancouver:

Sinha S. Robust dynamic optimization: theory and applications. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2020 Jan 21]. Available from: http://hdl.handle.net/1773/42949.

Council of Science Editors:

Sinha S. Robust dynamic optimization: theory and applications. [Doctoral Dissertation]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/42949


The Ohio State University

10. Rahimian, Hamed. Risk-Averse and Distributionally Robust Optimization:Methodology and Applications.

Degree: PhD, Industrial and Systems Engineering, 2018, The Ohio State University

 Many decision-making problems arising in science, engineering, and business involveuncertainties. One way to address these problems is to use stochastic optimization.A crucial task when building… (more)

Subjects/Keywords: Operations Research; Industrial Engineering; Decision-Making under Uncertainty, Mathematical Programming, Stochastic Optimization, Risk-Averse Optimization, Distributionally Robust Optimization

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APA (6th Edition):

Rahimian, H. (2018). Risk-Averse and Distributionally Robust Optimization:Methodology and Applications. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1531822931371766

Chicago Manual of Style (16th Edition):

Rahimian, Hamed. “Risk-Averse and Distributionally Robust Optimization:Methodology and Applications.” 2018. Doctoral Dissertation, The Ohio State University. Accessed January 21, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1531822931371766.

MLA Handbook (7th Edition):

Rahimian, Hamed. “Risk-Averse and Distributionally Robust Optimization:Methodology and Applications.” 2018. Web. 21 Jan 2020.

Vancouver:

Rahimian H. Risk-Averse and Distributionally Robust Optimization:Methodology and Applications. [Internet] [Doctoral dissertation]. The Ohio State University; 2018. [cited 2020 Jan 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1531822931371766.

Council of Science Editors:

Rahimian H. Risk-Averse and Distributionally Robust Optimization:Methodology and Applications. [Doctoral Dissertation]. The Ohio State University; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1531822931371766


University of Washington

11. Ajdari, Ali. Robust, Non-stationary, and Adaptive Fractionation in Radiotherapy.

Degree: PhD, 2018, University of Washington

 In external beam radiotherapy for cancer, high-energy radiation is passed through the pa- tient’s body from an outside source to kill tumor cells. The challenge… (more)

Subjects/Keywords: Adaptive treatment planning; Convex; Dynamic optimization; IMRT; Radiation therapy; Robust optimization; Industrial engineering; Operations research; Oncology; Industrial engineering

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APA (6th Edition):

Ajdari, A. (2018). Robust, Non-stationary, and Adaptive Fractionation in Radiotherapy. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/40917

Chicago Manual of Style (16th Edition):

Ajdari, Ali. “Robust, Non-stationary, and Adaptive Fractionation in Radiotherapy.” 2018. Doctoral Dissertation, University of Washington. Accessed January 21, 2020. http://hdl.handle.net/1773/40917.

MLA Handbook (7th Edition):

Ajdari, Ali. “Robust, Non-stationary, and Adaptive Fractionation in Radiotherapy.” 2018. Web. 21 Jan 2020.

Vancouver:

Ajdari A. Robust, Non-stationary, and Adaptive Fractionation in Radiotherapy. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2020 Jan 21]. Available from: http://hdl.handle.net/1773/40917.

Council of Science Editors:

Ajdari A. Robust, Non-stationary, and Adaptive Fractionation in Radiotherapy. [Doctoral Dissertation]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/40917


Georgia Tech

12. 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 January 21, 2020. 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. 21 Jan 2020.

Vancouver:

Lorca Galvez AH. Robust optimization for renewable energy integration in power system operations. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2020 Jan 21]. 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


University of Florida

13. Zhao, Kun. Mixed Integer Programming Approaches to 0-1 Knapsack Problems and Unified Stochastic and Robust Optimization on Wind Power Investment.

Degree: PhD, Industrial and Systems Engineering, 2015, University of Florida

 This dissertation covers a theoretical study of combining dynamic programming approach with cutting planes to solve the binary knapsack problems. In addition, motivated by the… (more)

Subjects/Keywords: Algorithms; Financial investments; Investment decisions; Linear programming; Operations research; Optimal solutions; Robust optimization; Run time; Transmission lines; Wind power; 0-1kp  – dynamic-programming  – mixed-integer  – optimization  – robust  – stochastic  – wind-power

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APA (6th Edition):

Zhao, K. (2015). Mixed Integer Programming Approaches to 0-1 Knapsack Problems and Unified Stochastic and Robust Optimization on Wind Power Investment. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0049286

Chicago Manual of Style (16th Edition):

Zhao, Kun. “Mixed Integer Programming Approaches to 0-1 Knapsack Problems and Unified Stochastic and Robust Optimization on Wind Power Investment.” 2015. Doctoral Dissertation, University of Florida. Accessed January 21, 2020. http://ufdc.ufl.edu/UFE0049286.

MLA Handbook (7th Edition):

Zhao, Kun. “Mixed Integer Programming Approaches to 0-1 Knapsack Problems and Unified Stochastic and Robust Optimization on Wind Power Investment.” 2015. Web. 21 Jan 2020.

Vancouver:

Zhao K. Mixed Integer Programming Approaches to 0-1 Knapsack Problems and Unified Stochastic and Robust Optimization on Wind Power Investment. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2020 Jan 21]. Available from: http://ufdc.ufl.edu/UFE0049286.

Council of Science Editors:

Zhao K. Mixed Integer Programming Approaches to 0-1 Knapsack Problems and Unified Stochastic and Robust Optimization on Wind Power Investment. [Doctoral Dissertation]. University of Florida; 2015. Available from: http://ufdc.ufl.edu/UFE0049286


University of California – Berkeley

14. Jain, Ankit. Topics in Modeling Uncertainty with Learning.

Degree: Industrial Engineering & Operations Research, 2010, University of California – Berkeley

 It is fair to say that in many real world decision problems the underlying models cannot be accurately represented. Uncertainty in a model may arise… (more)

Subjects/Keywords: Operations research; Industrial engineering; Statistics; Model Uncertainty; Non-parametric Learning; Operational Learning; Operational Statistics; Queuing Control; Robust optimization

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APA (6th Edition):

Jain, A. (2010). Topics in Modeling Uncertainty with Learning. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/6ng0c9tn

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):

Jain, Ankit. “Topics in Modeling Uncertainty with Learning.” 2010. Thesis, University of California – Berkeley. Accessed January 21, 2020. http://www.escholarship.org/uc/item/6ng0c9tn.

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

MLA Handbook (7th Edition):

Jain, Ankit. “Topics in Modeling Uncertainty with Learning.” 2010. Web. 21 Jan 2020.

Vancouver:

Jain A. Topics in Modeling Uncertainty with Learning. [Internet] [Thesis]. University of California – Berkeley; 2010. [cited 2020 Jan 21]. Available from: http://www.escholarship.org/uc/item/6ng0c9tn.

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

Council of Science Editors:

Jain A. Topics in Modeling Uncertainty with Learning. [Thesis]. University of California – Berkeley; 2010. Available from: http://www.escholarship.org/uc/item/6ng0c9tn

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


University of California – Berkeley

15. Chuang, Frank. Fast Predictive Control of Networked Energy Systems.

Degree: Mechanical Engineering, 2015, University of California – Berkeley

 In this thesis we study the optimal control of networked energy systems. Networked energy systems consist of a collection of energy storage nodes and a… (more)

Subjects/Keywords: Mechanical engineering; Mathematics; Operations research; Building HVAC systems; Model predictive control; Model reduction; Networked energy systems; Optimization; Robust control

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APA (6th Edition):

Chuang, F. (2015). Fast Predictive Control of Networked Energy Systems. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/4p87x9tc

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):

Chuang, Frank. “Fast Predictive Control of Networked Energy Systems.” 2015. Thesis, University of California – Berkeley. Accessed January 21, 2020. http://www.escholarship.org/uc/item/4p87x9tc.

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

MLA Handbook (7th Edition):

Chuang, Frank. “Fast Predictive Control of Networked Energy Systems.” 2015. Web. 21 Jan 2020.

Vancouver:

Chuang F. Fast Predictive Control of Networked Energy Systems. [Internet] [Thesis]. University of California – Berkeley; 2015. [cited 2020 Jan 21]. Available from: http://www.escholarship.org/uc/item/4p87x9tc.

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

Council of Science Editors:

Chuang F. Fast Predictive Control of Networked Energy Systems. [Thesis]. University of California – Berkeley; 2015. Available from: http://www.escholarship.org/uc/item/4p87x9tc

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

16. Ingram, Elijah E. Mitigating the impact of gifts-in-kind: an approach to strategic humanitarian response planning using robust facility location.

Degree: MS, Department of Industrial and Manufacturing Systems Engineering, 2013, Kansas State University

 Gifts-in-kind (GIK) donations negatively affect the humanitarian supply chain at the point of receipt near the disaster site. In any disaster, as much as 50… (more)

Subjects/Keywords: Humanitarian response; Gifts-in-kind; Facility location; Robust optimization; Industrial Engineering (0546); Mathematics (0405); Operations Research (0796)

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

APA (6th Edition):

Ingram, E. E. (2013). Mitigating the impact of gifts-in-kind: an approach to strategic humanitarian response planning using robust facility location. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/15556

Chicago Manual of Style (16th Edition):

Ingram, Elijah E. “Mitigating the impact of gifts-in-kind: an approach to strategic humanitarian response planning using robust facility location.” 2013. Masters Thesis, Kansas State University. Accessed January 21, 2020. http://hdl.handle.net/2097/15556.

MLA Handbook (7th Edition):

Ingram, Elijah E. “Mitigating the impact of gifts-in-kind: an approach to strategic humanitarian response planning using robust facility location.” 2013. Web. 21 Jan 2020.

Vancouver:

Ingram EE. Mitigating the impact of gifts-in-kind: an approach to strategic humanitarian response planning using robust facility location. [Internet] [Masters thesis]. Kansas State University; 2013. [cited 2020 Jan 21]. Available from: http://hdl.handle.net/2097/15556.

Council of Science Editors:

Ingram EE. Mitigating the impact of gifts-in-kind: an approach to strategic humanitarian response planning using robust facility location. [Masters Thesis]. Kansas State University; 2013. Available from: http://hdl.handle.net/2097/15556


University of Washington

17. Gong, Jue. Optimizing Personalized Treatment Selection for Partially Observable Chronic Conditions.

Degree: PhD, 2019, University of Washington

 For many chronic diseases, an individual patient may experience a wide variety of progres- sion pathways. Personalized medicine needs tools to predict the trajectory of… (more)

Subjects/Keywords: depression; medical decision making; partially observable Markov Decision Process; robust optimization; Industrial engineering; Operations research; Industrial engineering

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APA (6th Edition):

Gong, J. (2019). Optimizing Personalized Treatment Selection for Partially Observable Chronic Conditions. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/44326

Chicago Manual of Style (16th Edition):

Gong, Jue. “Optimizing Personalized Treatment Selection for Partially Observable Chronic Conditions.” 2019. Doctoral Dissertation, University of Washington. Accessed January 21, 2020. http://hdl.handle.net/1773/44326.

MLA Handbook (7th Edition):

Gong, Jue. “Optimizing Personalized Treatment Selection for Partially Observable Chronic Conditions.” 2019. Web. 21 Jan 2020.

Vancouver:

Gong J. Optimizing Personalized Treatment Selection for Partially Observable Chronic Conditions. [Internet] [Doctoral dissertation]. University of Washington; 2019. [cited 2020 Jan 21]. Available from: http://hdl.handle.net/1773/44326.

Council of Science Editors:

Gong J. Optimizing Personalized Treatment Selection for Partially Observable Chronic Conditions. [Doctoral Dissertation]. University of Washington; 2019. Available from: http://hdl.handle.net/1773/44326


University of Washington

18. Kotas, Jakob. Dynamic, convex, and robust optimization with Bayesian learning for response-guided dosing.

Degree: PhD, 2016, University of Washington

 Medical treatment commonly involves the administration of drug doses at multiple time-points. Intuitively, the higher the doses, the higher the likelihood of disease control as… (more)

Subjects/Keywords: Bayesian learning; Convex optimization; Dynamic programming; Medical decision-making; Response-guided dosing; Robust optimization; Applied mathematics; Industrial engineering; Operations research; applied mathematics

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APA (6th Edition):

Kotas, J. (2016). Dynamic, convex, and robust optimization with Bayesian learning for response-guided dosing. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/36482

Chicago Manual of Style (16th Edition):

Kotas, Jakob. “Dynamic, convex, and robust optimization with Bayesian learning for response-guided dosing.” 2016. Doctoral Dissertation, University of Washington. Accessed January 21, 2020. http://hdl.handle.net/1773/36482.

MLA Handbook (7th Edition):

Kotas, Jakob. “Dynamic, convex, and robust optimization with Bayesian learning for response-guided dosing.” 2016. Web. 21 Jan 2020.

Vancouver:

Kotas J. Dynamic, convex, and robust optimization with Bayesian learning for response-guided dosing. [Internet] [Doctoral dissertation]. University of Washington; 2016. [cited 2020 Jan 21]. Available from: http://hdl.handle.net/1773/36482.

Council of Science Editors:

Kotas J. Dynamic, convex, and robust optimization with Bayesian learning for response-guided dosing. [Doctoral Dissertation]. University of Washington; 2016. Available from: http://hdl.handle.net/1773/36482


University of Michigan

19. Guo, Yuanyuan. Data-Driven Distributionally Robust Optimization for Power System Operations.

Degree: PhD, Industrial & Operations Engineering, 2019, University of Michigan

 Decisions are often made in an uncertain environment. For example, in power system operations, decision makers need to schedule generators without the accurate outcome of… (more)

Subjects/Keywords: Optimization under Uncertainty; Distributionally Robust Optimization; Power System Operations; Industrial and Operations Engineering; Engineering

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APA (6th Edition):

Guo, Y. (2019). Data-Driven Distributionally Robust Optimization for Power System Operations. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/151535

Chicago Manual of Style (16th Edition):

Guo, Yuanyuan. “Data-Driven Distributionally Robust Optimization for Power System Operations.” 2019. Doctoral Dissertation, University of Michigan. Accessed January 21, 2020. http://hdl.handle.net/2027.42/151535.

MLA Handbook (7th Edition):

Guo, Yuanyuan. “Data-Driven Distributionally Robust Optimization for Power System Operations.” 2019. Web. 21 Jan 2020.

Vancouver:

Guo Y. Data-Driven Distributionally Robust Optimization for Power System Operations. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2020 Jan 21]. Available from: http://hdl.handle.net/2027.42/151535.

Council of Science Editors:

Guo Y. Data-Driven Distributionally Robust Optimization for Power System Operations. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/151535


UCLA

20. Rath, Sandeep. Resource Planning Models for Healthcare Organizations.

Degree: Management (MS/PHD), 2016, UCLA

 In this dissertation I look at two problems of resource planning at two major healthcare organizations. The Greater Los Angeles Station of the Veterans Health… (more)

Subjects/Keywords: Management; Operations research; Healthcare Operations; Optimization

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APA (6th Edition):

Rath, S. (2016). Resource Planning Models for Healthcare Organizations. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/7mv3p3dn

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):

Rath, Sandeep. “Resource Planning Models for Healthcare Organizations.” 2016. Thesis, UCLA. Accessed January 21, 2020. http://www.escholarship.org/uc/item/7mv3p3dn.

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

MLA Handbook (7th Edition):

Rath, Sandeep. “Resource Planning Models for Healthcare Organizations.” 2016. Web. 21 Jan 2020.

Vancouver:

Rath S. Resource Planning Models for Healthcare Organizations. [Internet] [Thesis]. UCLA; 2016. [cited 2020 Jan 21]. Available from: http://www.escholarship.org/uc/item/7mv3p3dn.

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

Council of Science Editors:

Rath S. Resource Planning Models for Healthcare Organizations. [Thesis]. UCLA; 2016. Available from: http://www.escholarship.org/uc/item/7mv3p3dn

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


The Ohio State University

21. Liu, Jianzhe. On Control and Optimization of DC Microgrids.

Degree: PhD, Electrical and Computer Engineering, 2017, The Ohio State University

 The power system is provisioned to evolve into a smart grid that is greener, safer, and more efficient. DC microgrid, a new form of distribution… (more)

Subjects/Keywords: Energy; Engineering; Electrical Engineering; Operations Research; power system, DC microgrids, constant power loads, network control, robust stability and control, decentralized control, stochastic optimization, chance constraint programming

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

APA (6th Edition):

Liu, J. (2017). On Control and Optimization of DC Microgrids. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1512049527948171

Chicago Manual of Style (16th Edition):

Liu, Jianzhe. “On Control and Optimization of DC Microgrids.” 2017. Doctoral Dissertation, The Ohio State University. Accessed January 21, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1512049527948171.

MLA Handbook (7th Edition):

Liu, Jianzhe. “On Control and Optimization of DC Microgrids.” 2017. Web. 21 Jan 2020.

Vancouver:

Liu J. On Control and Optimization of DC Microgrids. [Internet] [Doctoral dissertation]. The Ohio State University; 2017. [cited 2020 Jan 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1512049527948171.

Council of Science Editors:

Liu J. On Control and Optimization of DC Microgrids. [Doctoral Dissertation]. The Ohio State University; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1512049527948171

22. Froger, Aurélien. Maintenance scheduling in the electricity industry : a particular focus on a problem rising in the onshore wind industry : Planification de la maintenance d’équipements de production d’électricité : une attention particulière portée sur un problème de l’industrie éolienne terrestre.

Degree: Docteur es, Informatique, 2016, Angers

L’optimisation de la planification de la maintenance des équipements de production d’électricité est une question importante pour éviter des temps d’arrêt inutiles et des coûts… (more)

Subjects/Keywords: Éolien terrestre; Branch-And-Check; Optimisation robuste; Operations research; Scheduling; Maintenance in the electricity industry; Onshore wind farms; Integer linear programming; Constraint programming; Branch-And-Check; Robust optimization; 004

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APA (6th Edition):

Froger, A. (2016). Maintenance scheduling in the electricity industry : a particular focus on a problem rising in the onshore wind industry : Planification de la maintenance d’équipements de production d’électricité : une attention particulière portée sur un problème de l’industrie éolienne terrestre. (Doctoral Dissertation). Angers. Retrieved from http://www.theses.fr/2016ANGE0011

Chicago Manual of Style (16th Edition):

Froger, Aurélien. “Maintenance scheduling in the electricity industry : a particular focus on a problem rising in the onshore wind industry : Planification de la maintenance d’équipements de production d’électricité : une attention particulière portée sur un problème de l’industrie éolienne terrestre.” 2016. Doctoral Dissertation, Angers. Accessed January 21, 2020. http://www.theses.fr/2016ANGE0011.

MLA Handbook (7th Edition):

Froger, Aurélien. “Maintenance scheduling in the electricity industry : a particular focus on a problem rising in the onshore wind industry : Planification de la maintenance d’équipements de production d’électricité : une attention particulière portée sur un problème de l’industrie éolienne terrestre.” 2016. Web. 21 Jan 2020.

Vancouver:

Froger A. Maintenance scheduling in the electricity industry : a particular focus on a problem rising in the onshore wind industry : Planification de la maintenance d’équipements de production d’électricité : une attention particulière portée sur un problème de l’industrie éolienne terrestre. [Internet] [Doctoral dissertation]. Angers; 2016. [cited 2020 Jan 21]. Available from: http://www.theses.fr/2016ANGE0011.

Council of Science Editors:

Froger A. Maintenance scheduling in the electricity industry : a particular focus on a problem rising in the onshore wind industry : Planification de la maintenance d’équipements de production d’électricité : une attention particulière portée sur un problème de l’industrie éolienne terrestre. [Doctoral Dissertation]. Angers; 2016. Available from: http://www.theses.fr/2016ANGE0011


Università della Svizzera italiana

23. 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 January 21, 2020. 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. 21 Jan 2020.

Vancouver:

Mutsanas N. Approximability of precedence constrained and robust scheduling problems. [Internet] [Thesis]. Università della Svizzera italiana; 2010. [cited 2020 Jan 21]. 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


ETH Zürich

24. Zemmer, Kevin. Integer Polynomial Optimization in Fixed Dimension.

Degree: 2017, ETH Zürich

 The problem of optimizing multivariate scalar polynomial functions over mixed-integer points in polyhedra is a generalization of the well known Linear Programming (LP) problem. While… (more)

Subjects/Keywords: Operations Research; Mathematical Optimization; Integer Optimization; Polynomial Optimization; Fixed Dimension

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APA (6th Edition):

Zemmer, K. (2017). Integer Polynomial Optimization in Fixed Dimension. (Doctoral Dissertation). ETH Zürich. Retrieved from http://hdl.handle.net/20.500.11850/241796

Chicago Manual of Style (16th Edition):

Zemmer, Kevin. “Integer Polynomial Optimization in Fixed Dimension.” 2017. Doctoral Dissertation, ETH Zürich. Accessed January 21, 2020. http://hdl.handle.net/20.500.11850/241796.

MLA Handbook (7th Edition):

Zemmer, Kevin. “Integer Polynomial Optimization in Fixed Dimension.” 2017. Web. 21 Jan 2020.

Vancouver:

Zemmer K. Integer Polynomial Optimization in Fixed Dimension. [Internet] [Doctoral dissertation]. ETH Zürich; 2017. [cited 2020 Jan 21]. Available from: http://hdl.handle.net/20.500.11850/241796.

Council of Science Editors:

Zemmer K. Integer Polynomial Optimization in Fixed Dimension. [Doctoral Dissertation]. ETH Zürich; 2017. Available from: http://hdl.handle.net/20.500.11850/241796


Columbia University

25. Qiu, Zhen. Approximation Algorithms for Demand-Response Contract Execution and Coflow Scheduling.

Degree: 2016, Columbia University

 Solving operations research problems with approximation algorithms has been an important topic since approximation algorithm can provide near-optimal solutions to NP-hard problems while achieving computational… (more)

Subjects/Keywords: Approximation algorithms; Mathematical optimization; Scheduling; Operations research

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APA (6th Edition):

Qiu, Z. (2016). Approximation Algorithms for Demand-Response Contract Execution and Coflow Scheduling. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8FQ9WVP

Chicago Manual of Style (16th Edition):

Qiu, Zhen. “Approximation Algorithms for Demand-Response Contract Execution and Coflow Scheduling.” 2016. Doctoral Dissertation, Columbia University. Accessed January 21, 2020. https://doi.org/10.7916/D8FQ9WVP.

MLA Handbook (7th Edition):

Qiu, Zhen. “Approximation Algorithms for Demand-Response Contract Execution and Coflow Scheduling.” 2016. Web. 21 Jan 2020.

Vancouver:

Qiu Z. Approximation Algorithms for Demand-Response Contract Execution and Coflow Scheduling. [Internet] [Doctoral dissertation]. Columbia University; 2016. [cited 2020 Jan 21]. Available from: https://doi.org/10.7916/D8FQ9WVP.

Council of Science Editors:

Qiu Z. Approximation Algorithms for Demand-Response Contract Execution and Coflow Scheduling. [Doctoral Dissertation]. Columbia University; 2016. Available from: https://doi.org/10.7916/D8FQ9WVP


Columbia University

26. Feigenbaum, Itai Izhak. Optimization in Strategic Environments.

Degree: 2016, Columbia University

 This work considers the problem faced by a decision maker (planner) trying to optimize over incomplete data. The missing data is privately held by agents… (more)

Subjects/Keywords: Mathematical optimization; Algorithms; Planners; Operations research

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APA (6th Edition):

Feigenbaum, I. I. (2016). Optimization in Strategic Environments. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8377916

Chicago Manual of Style (16th Edition):

Feigenbaum, Itai Izhak. “Optimization in Strategic Environments.” 2016. Doctoral Dissertation, Columbia University. Accessed January 21, 2020. https://doi.org/10.7916/D8377916.

MLA Handbook (7th Edition):

Feigenbaum, Itai Izhak. “Optimization in Strategic Environments.” 2016. Web. 21 Jan 2020.

Vancouver:

Feigenbaum II. Optimization in Strategic Environments. [Internet] [Doctoral dissertation]. Columbia University; 2016. [cited 2020 Jan 21]. Available from: https://doi.org/10.7916/D8377916.

Council of Science Editors:

Feigenbaum II. Optimization in Strategic Environments. [Doctoral Dissertation]. Columbia University; 2016. Available from: https://doi.org/10.7916/D8377916


Cornell University

27. Lo, Venus Hiu Ling. Capturing Product Complementarity in Assortment Optimization .

Degree: 2019, Cornell University

 We study three assortment optimization problems that reflect the current retail environment. The goal of these problems is to compute an assortment which maximizes the… (more)

Subjects/Keywords: Operations research; assortment optimization; revenue management

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APA (6th Edition):

Lo, V. H. L. (2019). Capturing Product Complementarity in Assortment Optimization . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/67280

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):

Lo, Venus Hiu Ling. “Capturing Product Complementarity in Assortment Optimization .” 2019. Thesis, Cornell University. Accessed January 21, 2020. http://hdl.handle.net/1813/67280.

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

MLA Handbook (7th Edition):

Lo, Venus Hiu Ling. “Capturing Product Complementarity in Assortment Optimization .” 2019. Web. 21 Jan 2020.

Vancouver:

Lo VHL. Capturing Product Complementarity in Assortment Optimization . [Internet] [Thesis]. Cornell University; 2019. [cited 2020 Jan 21]. Available from: http://hdl.handle.net/1813/67280.

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

Council of Science Editors:

Lo VHL. Capturing Product Complementarity in Assortment Optimization . [Thesis]. Cornell University; 2019. Available from: http://hdl.handle.net/1813/67280

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


University of Arkansas

28. Heydari, Mohammadhossein. Optimal Allocation of Resources in Reliability Growth.

Degree: PhD, 2018, University of Arkansas

  Reliability growth testing seeks to identify and remove failure modes in order to improve system reliability. This dissertation centers around the resource allocation across… (more)

Subjects/Keywords: Reliability Growth; Resource Allocation; Robust Optimization; Industrial Engineering; Operational Research

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APA (6th Edition):

Heydari, M. (2018). Optimal Allocation of Resources in Reliability Growth. (Doctoral Dissertation). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/2688

Chicago Manual of Style (16th Edition):

Heydari, Mohammadhossein. “Optimal Allocation of Resources in Reliability Growth.” 2018. Doctoral Dissertation, University of Arkansas. Accessed January 21, 2020. https://scholarworks.uark.edu/etd/2688.

MLA Handbook (7th Edition):

Heydari, Mohammadhossein. “Optimal Allocation of Resources in Reliability Growth.” 2018. Web. 21 Jan 2020.

Vancouver:

Heydari M. Optimal Allocation of Resources in Reliability Growth. [Internet] [Doctoral dissertation]. University of Arkansas; 2018. [cited 2020 Jan 21]. Available from: https://scholarworks.uark.edu/etd/2688.

Council of Science Editors:

Heydari M. Optimal Allocation of Resources in Reliability Growth. [Doctoral Dissertation]. University of Arkansas; 2018. Available from: https://scholarworks.uark.edu/etd/2688


Arizona State University

29. Korad, Akshay Shashikumar. Robust Corrective Topology Control for System Reliability and Renewable Integration.

Degree: Electrical Engineering, 2015, Arizona State University

Subjects/Keywords: Electrical engineering; Operations research; Engineering; power system operations; power system reliability; power system stability; renewable generation; robust optimization; topology control

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APA (6th Edition):

Korad, A. S. (2015). Robust Corrective Topology Control for System Reliability and Renewable Integration. (Doctoral Dissertation). Arizona State University. Retrieved from http://repository.asu.edu/items/29867

Chicago Manual of Style (16th Edition):

Korad, Akshay Shashikumar. “Robust Corrective Topology Control for System Reliability and Renewable Integration.” 2015. Doctoral Dissertation, Arizona State University. Accessed January 21, 2020. http://repository.asu.edu/items/29867.

MLA Handbook (7th Edition):

Korad, Akshay Shashikumar. “Robust Corrective Topology Control for System Reliability and Renewable Integration.” 2015. Web. 21 Jan 2020.

Vancouver:

Korad AS. Robust Corrective Topology Control for System Reliability and Renewable Integration. [Internet] [Doctoral dissertation]. Arizona State University; 2015. [cited 2020 Jan 21]. Available from: http://repository.asu.edu/items/29867.

Council of Science Editors:

Korad AS. Robust Corrective Topology Control for System Reliability and Renewable Integration. [Doctoral Dissertation]. Arizona State University; 2015. Available from: http://repository.asu.edu/items/29867


Université Paris-Sud – Paris XI

30. Excoffier, Mathilde. Chance-Constrained Programming Approaches for Staffing and Shift-Scheduling Problems with Uncertain Forecasts : application to Call Centers : Approches de programmation en contraintes en probabilité pour les problèmes de dimensionnement et planification avec incertitude de la demande : application aux centres d'appels.

Degree: Docteur es, Informatique, 2015, Université Paris-Sud – Paris XI

Le problème de dimensionnement et planification d'agents en centre d'appels consiste à déterminer sur une période le nombre d'interlocuteurs requis afin d'atteindre la qualité de… (more)

Subjects/Keywords: Optimisation mathématique; Recherche opérationnelle; Programmation stochastique; Optimisation robuste; Contraintes en probabilités; Théorie des files d'attente; Lois de probabilité continues; Programmation linéaire mixte; Mathematical Optimization; Operations Research; Stochastic Programming; Robust Optimization; Chance Constraints; Queuing Theory; Continuous Distributions; Mixed-Integer Linear Programming

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APA (6th Edition):

Excoffier, M. (2015). Chance-Constrained Programming Approaches for Staffing and Shift-Scheduling Problems with Uncertain Forecasts : application to Call Centers : Approches de programmation en contraintes en probabilité pour les problèmes de dimensionnement et planification avec incertitude de la demande : application aux centres d'appels. (Doctoral Dissertation). Université Paris-Sud – Paris XI. Retrieved from http://www.theses.fr/2015PA112244

Chicago Manual of Style (16th Edition):

Excoffier, Mathilde. “Chance-Constrained Programming Approaches for Staffing and Shift-Scheduling Problems with Uncertain Forecasts : application to Call Centers : Approches de programmation en contraintes en probabilité pour les problèmes de dimensionnement et planification avec incertitude de la demande : application aux centres d'appels.” 2015. Doctoral Dissertation, Université Paris-Sud – Paris XI. Accessed January 21, 2020. http://www.theses.fr/2015PA112244.

MLA Handbook (7th Edition):

Excoffier, Mathilde. “Chance-Constrained Programming Approaches for Staffing and Shift-Scheduling Problems with Uncertain Forecasts : application to Call Centers : Approches de programmation en contraintes en probabilité pour les problèmes de dimensionnement et planification avec incertitude de la demande : application aux centres d'appels.” 2015. Web. 21 Jan 2020.

Vancouver:

Excoffier M. Chance-Constrained Programming Approaches for Staffing and Shift-Scheduling Problems with Uncertain Forecasts : application to Call Centers : Approches de programmation en contraintes en probabilité pour les problèmes de dimensionnement et planification avec incertitude de la demande : application aux centres d'appels. [Internet] [Doctoral dissertation]. Université Paris-Sud – Paris XI; 2015. [cited 2020 Jan 21]. Available from: http://www.theses.fr/2015PA112244.

Council of Science Editors:

Excoffier M. Chance-Constrained Programming Approaches for Staffing and Shift-Scheduling Problems with Uncertain Forecasts : application to Call Centers : Approches de programmation en contraintes en probabilité pour les problèmes de dimensionnement et planification avec incertitude de la demande : application aux centres d'appels. [Doctoral Dissertation]. Université Paris-Sud – Paris XI; 2015. Available from: http://www.theses.fr/2015PA112244

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