期刊
JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE C-COMPUTERS & ELECTRONICS
卷 12, 期 7, 页码 589-596出版社
ZHEJIANG UNIV
DOI: 10.1631/jzus.C1000313
关键词
Extremal optimization (EO); Evolution; Probability distributions; Maximum satisfiability (MAXSAT) problem
类别
资金
- National Natural Science Foundation of China [61074045]
- National Basic Research Program (973) of China [2007CB714000]
- National Creative Research Groups Science Foundation of China [60721062]
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据