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利用改进的HBDE算法求解MAX-k-SAT问题
引用本文:宋建民,苟海燕.利用改进的HBDE算法求解MAX-k-SAT问题[J].河北省科学院学报,2014(1):1-7.
作者姓名:宋建民  苟海燕
作者单位:[1]石家庄经济学院数理学院,河北石家庄050031 [2]石家庄经济学院华信学院,河北新乐050700
基金项目:河北省教育厅高等学校科技研究项目(NO.Z2013110)
摘    要:目前,利用进化算法求解组合优化问题已成为智能计算领域中的研究热点。本文基于二进制差分演化算法和动态变邻域搜索相结合提出了一种求解最大可满足问题(MAX-k-SAT)的改进算法(记为IBDE),通过与遗传算法和Johnson算法对一系列随机大规模MAX-k-SAT实例的求解比较表明:IBDE是一种求解MAX-k-SAT问题非常有效的新方法。

关 键 词:二进制差分演化  变邻域搜索  组合优化问题  MAX-SAT问题

Solving MAX-k-SAT Problems by Improved HBDE Algorithm
SONG Jian-min,GOU Hai-yan.Solving MAX-k-SAT Problems by Improved HBDE Algorithm[J].Journal of The Hebei Academy of Sciences,2014(1):1-7.
Authors:SONG Jian-min  GOU Hai-yan
Affiliation:1. College of Mathematics and Sciences, Shijiazhuang University of Economics, Shijiazhuang Hebei 050031, China ; 2. Huaxin College, Shijiazhuang University of Economics, Xinle Hebei 050700, China)
Abstract:At present,the evolutionary algorithm for solving combinatorial optimization problems has become a hot research topic in the field of intelligent computation.In this paper,we advance an improved binary differential evolution algorithm(denoted as IBDE)which combinations the binary differential evolution algorithm with dynamic variable neighborhood search for solving the maximum satisfiability problem(MAX-k-SAT).For a series of random largescale instances of MAX-k-SAT,the computational results of IBDE,Genetic algorithm and Johnson algorithm show that:IBDE is a new effective algorithm for MAX-k-SAT.
Keywords:Binary differential evolution  Variable neighborhood search  Combinational optimization problems  MAX-SAT problem
本文献已被 CNKI 维普 等数据库收录!
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