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Main Title: Optimization over Integers with Robustness in Cost and Few Constraints
Author(s): Goetzmann, Kai-Simon
Stiller, Sebastian
Telha, Claudio
Type: Research Paper
URI: https://depositonce.tu-berlin.de/handle/11303/15722
http://dx.doi.org/10.14279/depositonce-14495
License: http://rightsstatements.org/vocab/InC/1.0/
Abstract: Robust optimization is an approach for optimization under uncertainty that has recently attracted attention both from theory and practitioners. While there is an elaborate and powerful machinery for continuous robust optimization problems, results on robust combinatorial optimization and robust linear integer programs are still rare and hardly general. In a seminal paper Bertsimas and Sim (2003) show that for an arbitrary, linear 0-1-problem, over which one can optimize, one can also optimize the cost-robust counterpart. They explicitly note that this method is confined to binary problems. We present a result of this type for general integer programs. Further, we extend the result to integer programs with uncertainty in one constraint.
Subject(s): robust optimization
integer programming
Unbounded Knapsack
Issue Date: 2011
Date Available: 17-Dec-2021
Language Code: en
DDC Class: 510 Mathematik
Series: Preprint-Reihe des Instituts für Mathematik, Technische Universität Berlin
Series Number: 2011, 09
ISSN: 2197-8085
TU Affiliation(s): Fak. 2 Mathematik und Naturwissenschaften » Inst. Mathematik
Appears in Collections:Technische Universität Berlin » Publications

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