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A new initialization procedure for the distributed estimation of distribution algorithms

机译:分布算法分布估计的新初始化程序

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Estimation of distribution algorithms (EDAs) are one of the most promising paradigms in today’s evolutionary computation. In this field, there has been an incipient activity in the so-called parallel estimation of distribution algorithms (pEDAs). One of these approaches is the distributed estimation of distribution algorithms (dEDAs). This paper introduces a new initialization mechanism for each of the populations of the islands based on the Voronoi cells. To analyze the results, a series of different experiments using the benchmark suite for the special session on Real-parameter Optimization of the IEEE CEC 2005 conference has been carried out. The results obtained suggest that the Voronoi initialization method considerably improves the performance obtained from a traditional uniform initialization.
机译:分布算法(EDA)估计是当今进化计算中最有希望的范例之一。在这一领域,所谓的分布算法并行估计(pEDA)一直处于起步阶段。这些方法之一是分布算法(dEDA)的分布估计。本文介绍了一种基于Voronoi单元的岛上每个种群的新初始化机制。为了分析结果,已经针对IEEE CEC 2005大会的实参优化特别会议使用了基准套件进行了一系列不同的实验。获得的结果表明,Voronoi初始化方法大大提高了从传统的统一初始化获得的性能。

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