将最大团求解算法融入到极大团枚举算法中,提出了两种带极大团下限的极大团枚举算法及多种预处理筛选策略,通过迭代将不可能包含在极大团中的部分点与边删除,使得搜索空间大幅减小.在搜索策略上,将求解最大团问题的贪心染色算法、增量Ma...将最大团求解算法融入到极大团枚举算法中,提出了两种带极大团下限的极大团枚举算法及多种预处理筛选策略,通过迭代将不可能包含在极大团中的部分点与边删除,使得搜索空间大幅减小.在搜索策略上,将求解最大团问题的贪心染色算法、增量MaxSAT推理算法与极大团枚举算法相融合,并结合最佳筛选策略,提出了染色-关键点融合算法BKFC(Bron-Kerbosch with filtering and coloring)和基于增量MaxSAT推理的枚举算法BKFS(Bron-Kerbosch with filtering and MaxSAT).结果表明:在多个大型算例上,BKFC算法平均时间仅为加入预处理的改进经典算法的68.8%;由于经典算法无法在大型算例上运行,在小数据测试中,BKFC算法平均时间仅为没有预处理策略的经典算法的2.2%.展开更多
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) ...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.展开更多
文摘将最大团求解算法融入到极大团枚举算法中,提出了两种带极大团下限的极大团枚举算法及多种预处理筛选策略,通过迭代将不可能包含在极大团中的部分点与边删除,使得搜索空间大幅减小.在搜索策略上,将求解最大团问题的贪心染色算法、增量MaxSAT推理算法与极大团枚举算法相融合,并结合最佳筛选策略,提出了染色-关键点融合算法BKFC(Bron-Kerbosch with filtering and coloring)和基于增量MaxSAT推理的枚举算法BKFS(Bron-Kerbosch with filtering and MaxSAT).结果表明:在多个大型算例上,BKFC算法平均时间仅为加入预处理的改进经典算法的68.8%;由于经典算法无法在大型算例上运行,在小数据测试中,BKFC算法平均时间仅为没有预处理策略的经典算法的2.2%.
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)
文摘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.
