Clustering of moving vectors for evolutionary computation

Jun Yu, H. Takagi
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引用次数: 4

Abstract

We propose a method for clustering moving vectors oriented around two different local optima and some methods for improving the clustering performance. Evolutionary computation is an optimization method for finding the global optimum iteratively using multiple individuals; we propose a method for estimating the global optimum mathematically using the moving vectors between parent individuals and their offspring. Our proposed clustering method is the first to tackle the extension of the estimation method to multi-modal optimization. We describe the algorithm of the clustering method, the improvements made to the method, and the estimation performance for two local optima.
演化计算中运动向量的聚类
我们提出了一种围绕两个不同的局部最优的移动向量聚类方法和一些提高聚类性能的方法。进化计算是一种利用多个体迭代寻找全局最优解的优化方法;我们提出了一种利用亲本个体与子代之间的移动向量进行全局最优估计的数学方法。我们提出的聚类方法是第一个将估计方法扩展到多模态优化的方法。本文描述了聚类方法的算法,对方法的改进,以及对两个局部最优的估计性能。
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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