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Advanced Tabu Search Algorithms for Bipartite Boolean Quadratic Programs Guided by Strategic Oscillation and Path Relinking

机译:战略振荡和路径重新链接指导的二元布尔二次程序的高级禁忌搜索算法

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The bipartite Boolean quadratic programming problem (BBQP) is a generalization of the well-studied NP-hard Boolean quadratic programming problem and can be regarded as a unified model for many graph theoretic optimization problems, including maximum weight-induced subgraph problems, maximum weight biclique problems, matrix factorization problems, and maximum cut problems on bipartite graphs. This paper introduces three main algorithms for solving the BBQP, based on three variants of tabu search, the first two consisting of strategic oscillation-tabu search (SO-TS) algorithms, which use destructive and constructive procedures to guide the search into unexplored and promising areas. The third algorithm, whichDoes also incorporates the SO-TS algorithms as solution improvement methods, uses a path relinking (PR) algorithm that is capable of further enhancing search performance. Experimental results demonstrate that all three algorithms perform very effectively compared with the best methods in the literature, and the PR algorithm joined with tabu search is able to discover new best solutions for two-thirds of the large problem instances and match the previous best known solutions for the other instances. Additional analysis discloses the contributions of the key ingredients of each of the proposed algorithms.
机译:二元布尔二次规划问题(BBQP)是经过深入研究的NP-硬布尔二次规划问题的推广,可以看作许多图论优化问题的统一模型,包括最大权重诱发的子图问题,最大权重双斜体问题,矩阵分解问题和二部图上的最大割问题。本文基于禁忌搜索的三种变体,介绍了三种用于解决BBQP的主要算法,前两种由战略振荡-禁忌搜索(SO-TS)算法组成,它们使用破坏性和建设性的程序来引导搜索进入未开发和有前途的搜索地区。第三种算法也将SO-TS算法作为解决方案改进方法,该算法使用一种能够进一步增强搜索性能的路径重新链接(PR)算法。实验结果表明,与文献中的最佳方法相比,这三种算法的性能都非常有效,并且结合禁忌搜索的PR算法能够为三分之二的大型问题实例发现新的最佳解决方案,并与以前的最佳解决方案匹配对于其他情况。进一步的分析揭示了每个提出的算法的关键成分的贡献。

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