A comparative theoretical and computational study on robust counterpart optimization: II. Probabilistic guarantees on constraint satisfaction

Industrial and Engineering Chemistry Research

Volumn 51, Issue 19, 2012, Pages 6769-6788

  Li, Zukui ^a   Tang, Qiuhua ^b   Floudas, Christodoulos A ^a  

^a Princeton University   (United States)

^b WUHAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL STUDIES; CONSTRAINT SATISFACTION; MIXED-INTEGER LINEAR OPTIMIZATIONS; NUMERICAL STUDIES; OPTIMIZATION FORMULATIONS; OPTIMIZATION MODELS; PROBABILISTIC GUARANTEES; PROBABILITY BOUND; PROCESS-SCHEDULING PROBLEM; PRODUCTION PLANNING; ROBUST OPTIMIZATION; ROBUST SOLUTIONS;

OPTIMIZATION; PROBABILITY DISTRIBUTIONS; PRODUCTION CONTROL;

INTEGER PROGRAMMING;

EID: 84861168114     PISSN: 08885885     EISSN: 15205045     Source Type: Journal    
DOI: 10.1021/ie201651s     Document Type: Article

References (26)

1. Li, Z.; Ding, R.; Floudas, C.A. A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear and Robust Mixed Integer Linear Optimization. Ind. Eng. Chem. Res. 2011, 50, 10567
2. Soyster, A. L. Convex programming with set-inclusive constraints and applications to inexact linear programming Oper. Res. 1973, 21, 1154-1157
3. Ben-Tal, A.; Nemirovski, A. Robust solutions of uncertain linear programs Oper. Res. Lett. 1999, 25 (1) 1-13
4. Ben-Tal, A.; Nemirovski, A. Robust solutions of Linear Programming problems contaminated with uncertain data Math. Programming 2000, 88, 411-424
5. ElGhaoui, L.; Lebret, H. Robust solutions to least-squares problems with uncertain data Siam J. Matrix Anal. Appl. 1997, 18 (4) 1035-1064
6. El-Ghaoui, L.; Oustry, F.; Lebret, H. Robust solutions to uncertain semidefinite programs SIAM J. Optim. 1998, 9, 33-52
7. Bertsimas, D.; Sim, M. The price of robustness Oper. Res. 2004, 52 (1) 35-53
8. Lin, X.; Janak, S. L.; Floudas, C. A. A new robust optimization approach for scheduling under uncertainty: I. bounded uncertainty Comput. Chem. Eng. 2004, 28, 1069-1085
9. Janak, S. L.; Lin, X.; Floudas, C. A. A new robust optimization approach for scheduling under uncertainty: II. Uncertainty with known probability distribution Comput. Chem. Eng. 2007, 31, 171-195
10. Verderame, P. M.; Floudas, C. A. Operational planning of large-scale industrial batch plants under demand due date and amount uncertainty. I. Robust optimization framework Ind. Eng. Chem. Res. 2009, 48 (15) 7214-7231
11. Verderame, P. M.; Floudas, C. A. Operational planning of large-scale industrial batch plants under demand due date and amount uncertainty: II. Conditional value-at-risk framework Ind. Eng. Chem. Res. 2010, 49 (1) 260-275
12. Li, Z.; Ding, R.; Floudas, C. A. A comparative theoretical and computational study on robust counterpart optimization: I. Robust linear and robust mixed integer linear optimization Ind. Eng. Chem. Res. 2011, 50 (18) 10567-10603
13. El Ghaoui, L.; Oks, M.; Oustry, F. Worst-case value-at-risk and robust portfolio optimization: A conic programming approach Oper. Res. 2003, 51 (4) 543-556
14. Chen, X.; Sim, M.; Sun, P. A robust optimization perspective to stochastic programming Oper. Res. 2007, 55 (6) 1058-1071
15. Chen, W. Q.; Sim, M. Goal-driven optimization Oper. Res. 2009, 57 (2) 342-357
16. Delage, E.; Ye, Y. Distributionally robust optimization under moment uncertainty with application to data-driven problems Oper. Res. 2010, 58 (3) 595-612
17. Ben-Tal, A.; Bertsimas, D.; Brown, D. B. A soft robust model for optimization under ambiguity Oper. Res. 2010, 58 (4) 1220-1234
18. Bertsimas, D.; Pachamanova, D.; Sim, M. Robust linear optimization under general norms Oper. Res. Lett. 2004, 32 (6) 510-516
19. Bertsimas, D.; Sim, M. Tractable approximations to robust conic optimization problems Math. Programming 2006, 107 (1-2) 5-36
20. Paschalidis, I. C.; Kang, S.-C. In Robust Linear Optimization: On the Benefits of Distributional Information and Applications in Inventory Control, 44th IEEE Conference on Decision and Control, Seville, Spain, 2005; IEEE: Seville, Spain, 2005.
21. Ben-Tal, A.; Ghaoui, L. E.; Nemirovski, A. Robust Optimization; Princeton University Press: Princeton, NJ, 2009.
22. Ravindran, A. R. Operations Research Methodologies; CRC Press: New York, 2008.
23. Ierapetritou, M. G.; Floudas, C. A. Effective continuous-time formulation for short-term scheduling. 2. Continuous and semicontinuous processes Ind. Eng. Chem. Res. 1998, 37 (11) 4360-4374
24. Ierapetritou, M. G.; Floudas, C. A. Short-term scheduling: New mathematical models vs algorithmic improvements Comput. Chem. Eng. 1998, 22, S419-S426
25. Ierapetritou, M. G.; Hene, T. S.; Floudas, C. A. Effective continuous-time formulation for short-term scheduling. 3. Multiple intermediate due dates Ind. Eng. Chem. Res. 1999, 38 (9) 3446-3461
26. Hoeffding, W. Probability-inequalities for sums of bounded random-variables J. Am. Stat. Assoc. 1963, 58 (301) 13-30