Cooperative coevolutionary genetic algorithms to find optimal elimination orderings for Bayesian networks

Xuchu Dong, Haihong Yu, D. Ouyang, Dianbo Cai, Yuxin Ye, Yonggang Zhang
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引用次数: 3

Abstract

According to the characteristics of the optimal elimination ordering problem in Bayesian networks, a heuristic-based genetic algorithm, a cooperative coevolutionary genetic framework and five grouping schemes are proposed. Based on these works, six cooperative coevolutionary genetic algorithms are constructed. Numerical experiments show that these algorithms are more robust than other existing swarm intelligence methods when solving the elimination ordering problem.
寻找贝叶斯网络最优消除顺序的协同进化遗传算法
针对贝叶斯网络中最优消除排序问题的特点,提出了一种启发式遗传算法、一种协同进化遗传框架和五种分组方案。在此基础上,构建了6种协同进化遗传算法。数值实验表明,该算法在求解消去排序问题时比现有的群智能算法具有更强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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