最大权团问题的分支定界并行化算法

IF 0.9 4区 数学 Q3 MATHEMATICS, APPLIED Discrete Optimization Pub Date : 2021-08-01 DOI:10.1016/j.disopt.2021.100646
Satoshi Shimizu, Kazuaki Yamaguchi, Sumio Masuda
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引用次数: 2

摘要

本文对最大权值团问题的分支定界算法OTClique提出了并行化技术。OTClique由预计算阶段和分支绑定阶段组成。本文提出的算法将这两种算法并行化。在预计算阶段,最优表的构造是并行的。在分支绑定阶段,该算法生成小的子问题并将其分配给线程。提出了一种共享下界和上界的技术。使用一些基准测试的实验表明,所提出的并行化技术提高了OTClique的性能。使用8核CPU时,OTClique在随机图上的计算时间缩短了6.91倍,在DIMACS基准测试上的平均计算时间缩短了5.38倍。
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Parallelization of a branch-and-bound algorithm for the maximum weight clique problem

In this paper, parallelization techniques are proposed for the branch-and-bound algorithm OTClique for the maximum weight clique problem. OTClique consists of the precomputation phase and the branch-and-bound phase. The proposed algorithm parallelizes both of them. In the precomputation phase, the construction of optimal tables is parallelized. In the branch-and-bound phase, the proposed algorithm generates small subproblems and assigns them to threads. A technique to share lower and upper bounds is also proposed. Experiments using some benchmarks show that the proposed parallelization techniques improve the performance of OTClique. With an 8-core CPU, the computation time of OTClique becomes 6.91 times shorter on random graphs and 5.38 times on DIMACS benchmarks on average.

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来源期刊
Discrete Optimization
Discrete Optimization 管理科学-应用数学
CiteScore
2.10
自引率
9.10%
发文量
30
审稿时长
>12 weeks
期刊介绍: Discrete Optimization publishes research papers on the mathematical, computational and applied aspects of all areas of integer programming and combinatorial optimization. In addition to reports on mathematical results pertinent to discrete optimization, the journal welcomes submissions on algorithmic developments, computational experiments, and novel applications (in particular, large-scale and real-time applications). The journal also publishes clearly labelled surveys, reviews, short notes, and open problems. Manuscripts submitted for possible publication to Discrete Optimization should report on original research, should not have been previously published, and should not be under consideration for publication by any other journal.
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