Modified extremal optimization for the hard maximum satisfiability problem

被引：0
|
作者：
Guo-qiang ZENG 1
机构：
来源：
Frontiers of Information Technology & Electronic Engineering | 2011年 / 07期
基金：
中国国家自然科学基金;
关键词：
Extremal optimization (EO); Evolution; Probability distributions; Maximum satisfiability (MAXSAT) problem;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Based on our recent study on probability distributions for evolution in extremal optimization (EO),we propose a modified framework called EOSAT to approximate ground states of the hard maximum satisfiability (MAXSAT) problem,a generalized version of the satisfiability (SAT) problem.The basic idea behind EOSAT is to generalize the evolutionary probability distribution in the Bose-Einstein-EO (BE-EO) algorithm,competing with other popular algorithms such as simulated annealing and WALKSAT.Experimental results on the hard MAXSAT instances from SATLIB show that the modified algorithms are superior to the original BE-EO algorithm.
引用
收藏
页码：589 / 596
页数：8
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