Frameworks and Results in Distributionally Robust Optimization
The concepts of risk aversion, chance-constrained optimization, and robust optimization have developed significantly over the last decade. The statistical learning community has also witnessed a rapid theoretical and applied growth by relying on these concepts. A modeling framework, called distribut...
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| Format: | Article |
| Language: | English |
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Université de Montpellier
2022-07-01
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| Series: | Open Journal of Mathematical Optimization |
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| Online Access: | https://ojmo.centre-mersenne.org/articles/10.5802/ojmo.15/ |
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| _version_ | 1825204970676289536 |
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| author | Rahimian, Hamed Mehrotra, Sanjay |
| author_facet | Rahimian, Hamed Mehrotra, Sanjay |
| author_sort | Rahimian, Hamed |
| collection | DOAJ |
| description | The concepts of risk aversion, chance-constrained optimization, and robust optimization have developed significantly over the last decade. The statistical learning community has also witnessed a rapid theoretical and applied growth by relying on these concepts. A modeling framework, called distributionally robust optimization (DRO), has recently received significant attention in both the operations research and statistical learning communities. This paper surveys main concepts and contributions to DRO, and relationships with robust optimization, risk aversion, chance-constrained optimization, and function regularization. Various approaches to model the distributional ambiguity and their calibrations are discussed. The paper also describes the main solution techniques used to the solve the resulting optimization problems. |
| format | Article |
| id | doaj-art-5a012a72e0e54fb9996912c2d20ac319 |
| institution | Kabale University |
| issn | 2777-5860 |
| language | English |
| publishDate | 2022-07-01 |
| publisher | Université de Montpellier |
| record_format | Article |
| series | Open Journal of Mathematical Optimization |
| spelling | doaj-art-5a012a72e0e54fb9996912c2d20ac3192025-02-07T14:02:43ZengUniversité de MontpellierOpen Journal of Mathematical Optimization2777-58602022-07-01318510.5802/ojmo.1510.5802/ojmo.15Frameworks and Results in Distributionally Robust OptimizationRahimian, Hamed0Mehrotra, Sanjay1Department of Industrial Engineering, Clemson University, Clemson, SC 29634, USADepartment of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL 60208, USAThe concepts of risk aversion, chance-constrained optimization, and robust optimization have developed significantly over the last decade. The statistical learning community has also witnessed a rapid theoretical and applied growth by relying on these concepts. A modeling framework, called distributionally robust optimization (DRO), has recently received significant attention in both the operations research and statistical learning communities. This paper surveys main concepts and contributions to DRO, and relationships with robust optimization, risk aversion, chance-constrained optimization, and function regularization. Various approaches to model the distributional ambiguity and their calibrations are discussed. The paper also describes the main solution techniques used to the solve the resulting optimization problems.https://ojmo.centre-mersenne.org/articles/10.5802/ojmo.15/Distributionally robust optimizationRobust optimizationStochastic optimizationRisk-averse optimizationChance-constrained optimizationStatistical learning |
| spellingShingle | Rahimian, Hamed Mehrotra, Sanjay Frameworks and Results in Distributionally Robust Optimization Open Journal of Mathematical Optimization Distributionally robust optimization Robust optimization Stochastic optimization Risk-averse optimization Chance-constrained optimization Statistical learning |
| title | Frameworks and Results in Distributionally Robust Optimization |
| title_full | Frameworks and Results in Distributionally Robust Optimization |
| title_fullStr | Frameworks and Results in Distributionally Robust Optimization |
| title_full_unstemmed | Frameworks and Results in Distributionally Robust Optimization |
| title_short | Frameworks and Results in Distributionally Robust Optimization |
| title_sort | frameworks and results in distributionally robust optimization |
| topic | Distributionally robust optimization Robust optimization Stochastic optimization Risk-averse optimization Chance-constrained optimization Statistical learning |
| url | https://ojmo.centre-mersenne.org/articles/10.5802/ojmo.15/ |
| work_keys_str_mv | AT rahimianhamed frameworksandresultsindistributionallyrobustoptimization AT mehrotrasanjay frameworksandresultsindistributionallyrobustoptimization |