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作者机构:College of Physics & Electronic Information Engineering Wenzhou University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University
出 版 物:《Journal of Zhejiang University-Science C(Computers and Electronics)》 (浙江大学学报C辑(计算机与电子(英文版))
年 卷 期:2011年第12卷第7期
页 面:589-596页
核心收录:
学科分类:12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:supported by the National Natural Science Foundation of China (No.61074045) the National Basic Research Program (973) of China (No.2007CB714000) the National Creative Research Groups Science Foundation of China (No.60721062)
主 题:Extremal optimization (EO) Evolution Probability distributions Maximum satisfiability (MAXSAT) problem
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) *** 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 *** results on the hard MAXSAT instances from SATLIB show that the modified algorithms are superior to the original BE-EO algorithm.