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The Cartographer
Algorithms the min-max regret 0-1 Integer Linear Programming Problem with Interval Data
August 14, 2019 Β· Declared Dead Β· π arXiv.org
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Authors
Iago A. Carvalho, Thiago F. Noronha, Christophe Duhamel
arXiv ID
1908.05082
Category
cs.DS: Data Structures & Algorithms
Cross-listed
math.OC
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
We address the Interval Data Min-Max Regret 0-1 Integer Linear Programming problem (MMR-ILP), a variant of the 0-1 Integer Linear Programming problem where the objective function coefficients are uncertain. We solve MMR-ILP using a Benders-like Decomposition Algorithm and two metaheuristics for min-max regret problems with interval data. Computational experiments developed on variations of MIPLIB instances show that the heuristics obtain good results in a reasonable computational time when compared to the Benders-like Decomposition algorithm.
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