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On minimization of the number of branches in branch-and-bound algorithms for the maximum clique problem

机译:关于最大集团问题的分支定界算法中的分支数最小化

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摘要

When searching for a maximum clique in a graph G, branch-and-bound algorithms in the literature usually focus on the minimization of the number of branches generated at each search tree node. We call dynamic strategy this minimization without any constraint, because it induces a dynamic vertex ordering in G during the search. In this paper, we introduce a static strategy that minimizes the number of branches subject to the constraint that a static vertex ordering in G must be kept during the search. We analyze the two strategies and show that they are complementary. From this complementarity, we propose a new algorithm, called MoMC, that combines the strengths of the two strategies into a single algorithm. The reported experimental results show that MoMC is generally better than the algorithms implementing a single strategy. (C) 2017 Elsevier Ltd. All rights reserved.
机译:当在图G中搜索最大集团时,文献中的分支定界算法通常着重于最小化在每个搜索树节点处生成的分支数。我们称动态策略为没有任何约束的最小化,因为它在搜索过程中在G中引起动态顶点排序。在本文中,我们介绍了一种静态策略,该策略会在搜索过程中必须保留G中静态顶点顺序的约束下,最大限度地减少分支数量。我们分析了这两种策略,并证明它们是互补的。从这种互补性出发,我们提出了一种称为MoMC的新算法,该算法将两种策略的优势组合为一个算法。报告的实验结果表明,MoMC通常比实现单一策略的算法更好。 (C)2017 Elsevier Ltd.保留所有权利。

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