Two-stage robust mixed integer programming problem with objective uncertainty

被引：1
|
作者：
Zhang, Ning [1 ,2 ]
机构：
[1] Natl Univ Singapore, Dept Math, 10 Lower Kent Ridge Rd, Singapore 119076, Singapore
[2] Singapore ETH Ctr, Future Resilient Syst, 1 Create Way,CREATE Tower, Singapore 138602, Singapore
来源：
OPTIMIZATION LETTERS | 2018年 / 12卷 / 05期
关键词：
Two-stage robust optimization; Mixed integer programming; Objective uncertainty; Augmented Lagrangian; AFFINE POLICIES; ADAPTIVE OPTIMIZATION; DECISION RULES;
D O I：
10.1007/s11590-017-1176-z
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
Many real problems with uncertain parameters can be modeled as two-stage robust mixed integer programming problems (RMIPs). Due to the complex nature of this kind of problems, this paper focuses on the two-stage RMIPs with objective uncertainty. Based on the results that the augmented Lagrangian is a strong dual for integer programming Boland and Eberhard (Math Program 150(2):491-509, 2015), we present the upper and lower bounds. In a special case, we show that the two-stage RMIPs can be equivalently reformulated as a solvable minimax problem.
引用
收藏
页码：959 / 969
页数：11
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