A Comparison of Differential Evolution Algorithm with Binary and Continuous Encoding for the MKP

Jonas Krause, H. S. Lopes
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引用次数: 16

Abstract

This paper provides a brief description on how continuous algorithms can be applied to binary problems. Differential Evolution is the continuous algorithm studied and two versions of this algorithm are presented: the Binary Differential Evolution with a binary encoding and the Discretized Differential Evolution with a continuous encoding. Several discretization methods are presented and the most used method in literature is implemented for the solution discretization. Benchmarks with different complexity and search space sizes of the Multiple Knapsack Problem are used to compare the performance of each Differential Evolution algorithm presented and the Genetic Algorithm with binary encoding. Results suggest that continuous methods can be very efficient when discretized for binary spaces.
差分进化算法的二进编码与连续编码的比较
本文简要介绍了连续算法如何应用于二元问题。差分进化算法是一种连续算法,本文给出了该算法的两种版本:采用二进制编码的二元差分进化算法和采用连续编码的离散差分进化算法。提出了几种离散化方法,并将文献中最常用的方法用于解离散化。以不同复杂度和搜索空间大小的多背包问题为基准,比较了所提差分进化算法与二进制编码遗传算法的性能。结果表明,连续方法在二元空间离散化时是非常有效的。
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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