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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Veröffentlicht in:Optimization letters Jg. 12; H. 5; S. 959 - 969
1. Verfasser: Zhang, Ning
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2018
Schlagworte:
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-Zugang:Volltext
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Zusammenfassung: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