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Sequential Convex Approximations to Joint Chance Constrained Programs: A Monte Carlo Approach

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  1. Wim Ackooij, 2017. "A comparison of four approaches from stochastic programming for large-scale unit-commitment," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 119-147, March.
  2. Holger Berthold & Holger Heitsch & René Henrion & Jan Schwientek, 2022. "On the algorithmic solution of optimization problems subject to probabilistic/robust (probust) constraints," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 96(1), pages 1-37, August.
  3. Zhen, Chen & Zheng, Xiaoyong, 2015. "Measuring the Informational Value of Interpretive Shelf Nutrition Labels to Shoppers," 2016 Allied Social Sciences Association (ASSA) Annual Meeting, January 3-5, 2016, San Francisco, California 212812, Agricultural and Applied Economics Association.
  4. Zhou, Liping & Geng, Na & Jiang, Zhibin & Wang, Xiuxian, 2017. "Combining revenue and equity in capacity allocation of imaging facilities," European Journal of Operational Research, Elsevier, vol. 256(2), pages 619-628.
  5. Xiaodi Bai & Jie Sun & Xiaojin Zheng, 2021. "An Augmented Lagrangian Decomposition Method for Chance-Constrained Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1056-1069, July.
  6. L. Jeff Hong & Zhiyuan Huang & Henry Lam, 2021. "Learning-Based Robust Optimization: Procedures and Statistical Guarantees," Management Science, INFORMS, vol. 67(6), pages 3447-3467, June.
  7. L. Jeff Hong & Zhaolin Hu & Liwei Zhang, 2014. "Conditional Value-at-Risk Approximation to Value-at-Risk Constrained Programs: A Remedy via Monte Carlo," INFORMS Journal on Computing, INFORMS, vol. 26(2), pages 385-400, May.
  8. Álvaro Porras & Concepción Domínguez & Juan Miguel Morales & Salvador Pineda, 2023. "Tight and Compact Sample Average Approximation for Joint Chance-Constrained Problems with Applications to Optimal Power Flow," INFORMS Journal on Computing, INFORMS, vol. 35(6), pages 1454-1469, November.
  9. Sergey S. Rabotyagov & Adriana M. Valcu-Lisman & Catherine L. Kling, 2016. "Resilient Provision of Ecosystem Services from Agricultural Landscapes: Trade-offs Involving Means and Variances of Water Quality Improvements," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 98(5), pages 1295-1313.
  10. Zhiping Chen & Shen Peng & Abdel Lisser, 2020. "A sparse chance constrained portfolio selection model with multiple constraints," Journal of Global Optimization, Springer, vol. 77(4), pages 825-852, August.
  11. Feng Shan & Liwei Zhang & Xiantao Xiao, 2014. "A Smoothing Function Approach to Joint Chance-Constrained Programs," Journal of Optimization Theory and Applications, Springer, vol. 163(1), pages 181-199, October.
  12. Wang, Tingsong & Meng, Qiang & Wang, Shuaian & Tan, Zhijia, 2013. "Risk management in liner ship fleet deployment: A joint chance constrained programming model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 60(C), pages 1-12.
  13. Zheng, Xiaojin & Sun, Xiaoling & Li, Duan & Cui, Xueting, 2012. "Lagrangian decomposition and mixed-integer quadratic programming reformulations for probabilistically constrained quadratic programs," European Journal of Operational Research, Elsevier, vol. 221(1), pages 38-48.
  14. W. Ackooij & S. Demassey & P. Javal & H. Morais & W. Oliveira & B. Swaminathan, 2021. "A bundle method for nonsmooth DC programming with application to chance-constrained problems," Computational Optimization and Applications, Springer, vol. 78(2), pages 451-490, March.
  15. L. Jeff Hong & Jun Luo & Barry L. Nelson, 2015. "Chance Constrained Selection of the Best," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 317-334, May.
  16. Xiaojin Zheng & Xiaoling Sun & Duan Li & Jie Sun, 2014. "Successive convex approximations to cardinality-constrained convex programs: a piecewise-linear DC approach," Computational Optimization and Applications, Springer, vol. 59(1), pages 379-397, October.
  17. Welington Oliveira, 2019. "Proximal bundle methods for nonsmooth DC programming," Journal of Global Optimization, Springer, vol. 75(2), pages 523-563, October.
  18. Algo Carè & Simone Garatti & Marco C. Campi, 2014. "FAST---Fast Algorithm for the Scenario Technique," Operations Research, INFORMS, vol. 62(3), pages 662-671, June.
  19. Roya Karimi & Jianqiang Cheng & Miguel A. Lejeune, 2021. "A Framework for Solving Chance-Constrained Linear Matrix Inequality Programs," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1015-1036, July.
  20. Shao-Wei Lam & Tsan Sheng Ng & Melvyn Sim & Jin-Hwa Song, 2013. "Multiple Objectives Satisficing Under Uncertainty," Operations Research, INFORMS, vol. 61(1), pages 214-227, February.
  21. Zhaolin Hu & Jing Cao & L. Jeff Hong, 2012. "Robust Simulation of Global Warming Policies Using the DICE Model," Management Science, INFORMS, vol. 58(12), pages 2190-2206, December.
  22. Jia Wu & Yi Zhang & Liwei Zhang & Yue Lu, 2016. "A Sequential Convex Program Approach to an Inverse Linear Semidefinite Programming Problem," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(04), pages 1-26, August.
  23. Shen Peng & Jie Jiang, 2021. "Stochastic mathematical programs with probabilistic complementarity constraints: SAA and distributionally robust approaches," Computational Optimization and Applications, Springer, vol. 80(1), pages 153-184, September.
  24. Yuan Yuan & Zukui Li & Biao Huang, 2017. "Robust optimization approximation for joint chance constrained optimization problem," Journal of Global Optimization, Springer, vol. 67(4), pages 805-827, April.
  25. Hailin Sun & Huifu Xu & Yong Wang, 2014. "Asymptotic Analysis of Sample Average Approximation for Stochastic Optimization Problems with Joint Chance Constraints via Conditional Value at Risk and Difference of Convex Functions," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 257-284, April.
  26. Lukáš Adam & Martin Branda, 2016. "Nonlinear Chance Constrained Problems: Optimality Conditions, Regularization and Solvers," Journal of Optimization Theory and Applications, Springer, vol. 170(2), pages 419-436, August.
  27. Arash Gourtani & Tri-Dung Nguyen & Huifu Xu, 2020. "A distributionally robust optimization approach for two-stage facility location problems," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 8(2), pages 141-172, June.
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