Two-stage robust mixed integer programming problem with objective uncertainty

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...

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Bibliographic Details
Published in:	Optimization letters Vol. 12; no. 5; pp. 959 - 969
Main Author:	Zhang, Ning
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2018
Subjects:	Computational Intelligence Mathematics Mathematics and Statistics Numerical and Computational Physics Operations Research/Decision Theory Optimization Original Paper Simulation Mixed integer programming Objective uncertainty Two-stage robust optimization Augmented Lagrangian
ISSN:	1862-4472, 1862-4480
Online Access:	Get full text
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Summary:	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.
ISSN:	1862-4472 1862-4480
DOI:	10.1007/s11590-017-1176-z