分布估计算法的模型分析与研究

Analysis and Research Models of the Estimation of Distribution Algorithms

分布估计算法是在遗传算法基础上发展起来的一类新型进化优化算法。分布估计算法采用概率图模型表示基因变量之间的连锁关系,以构建优良解集的概率分布模型和采样分布模型来实现迭代优化。详细分析分布估计算法的基本原理,对采用不同概率图模型的分布估计算法进行总结和分析,并针对分布估计算法领域的研究现状,提出仍需解决的主要问题。

The Estimation of Distribution Algorithms （EDAs） is a novel class of evolutionary algorithms which is motivated by the idea of building probabilistic graphical model of promising solutions to represent linkage information between variables in chromosome. Through learning of and sampling from probabilistic graphical model, new population is generated and optimization procedure is repeated until the stopping criteria are met. In this paper, the mechanism of the Estimation of Distribution Algorithms is analyzed. Currently existing EDAs are surveyed and categorized according to the probabilistic model they used, then the strengths and weaknesses and the future perspective of EDAs are concluded.