首页> 外文会议>International Work-Conference on Artificial Neural Networks(IWANN 2005); 20050608-10; Barcelona(ES) >Cooperative Bees Swarm for Solving the Maximum Weighted Satisfiability Problem
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Cooperative Bees Swarm for Solving the Maximum Weighted Satisfiability Problem

机译:合作蜂群解决最大加权可满足性问题

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Solving a NP-Complete problem precisely is spiny: the combinative explosion is the ransom of this accurateness. It is the reason for which we have often resort to approached methods assuring the obtaining of a good solution in a reasonable time. In this paper we aim to introduce a new intelligent approach or meta-heuristic named "Bees Swarm Optimization", BSO for short, which is inspired from the behaviour of real bees. An adaptation to the features of the MAX-W-SAT problem is done to contribute to its resolution. We provide an overview of the results of empirical tests performed on the hard Johnson benchmark. A comparative study with well known procedures for MAX-W-SAT is done and shows that BSO outperforms the other evolutionary algorithms especially AC-SAT, an ant colony algorithm for SAT.
机译:精确地解决NP完全问题是棘手的:组合爆炸就是这种准确性的赎金。这就是我们经常诉诸于确保合理时间内获得良好解决方案的方法的原因。在本文中,我们旨在介绍一种新的智能方法或称为“蜜蜂群优化”的元启发式方法,简称BSO,其灵感来自于真实蜜蜂的行为。对MAX-W-SAT问题的特征进行了修改以有助于其解决。我们概述了在强生约翰逊基准测试中进行的经验测试的结果。对众所周知的MAX-W-SAT程序进行了比较研究,结果表明BSO优于其他进化算法,尤其是AC-SAT,后者是SAT的蚁群算法。

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