Parallelized Conflict Graph Cut Generation

Fuente: arXiv
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Main Authors: Dai, Yongzheng, Chen, Chen
Format: Preprint
Published: 2023
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author Dai, Yongzheng
Chen, Chen
author_facet Dai, Yongzheng
Chen, Chen
contents A conflict graph represents logical relations between binary variables, and effective use of the graph can significantly accelerate branch-and-cut solvers for mixed-integer programming (MIP). In this paper we develop efficient parallel conflict graph management: conflict detection; maximal clique generation; clique extension; and clique merging. We leverage parallel computing in order to intensify computational effort on the conflict graph, thereby generating a much larger pool of cutting planes than what can be practically achieved in serial. Computational experiments demonstrate that the expanded pool of cuts enabled by parallel computing lead to substantial reductions in total MIP solve time, especially for more challenging cases.
format Preprint
id arxiv_https___arxiv_org_abs_2311_03706
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Parallelized Conflict Graph Cut Generation
Dai, Yongzheng
Chen, Chen
Optimization and Control
90C10
A conflict graph represents logical relations between binary variables, and effective use of the graph can significantly accelerate branch-and-cut solvers for mixed-integer programming (MIP). In this paper we develop efficient parallel conflict graph management: conflict detection; maximal clique generation; clique extension; and clique merging. We leverage parallel computing in order to intensify computational effort on the conflict graph, thereby generating a much larger pool of cutting planes than what can be practically achieved in serial. Computational experiments demonstrate that the expanded pool of cuts enabled by parallel computing lead to substantial reductions in total MIP solve time, especially for more challenging cases.
title Parallelized Conflict Graph Cut Generation
topic Optimization and Control
90C10
url https://arxiv.org/abs/2311.03706