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

页码：959 / 969

页数：11

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