Differential evolution: Performances and analyses

N. Padhye, Pulkit Mittal, K. Deb
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引用次数: 28

Abstract

In this paper, we apply Differential Evolution (DE) algorithm in combination with a recently proposed constraint-handling strategy and study the performance 01' the resulting algorithm on CEC'13 test suite [1], and other constrained optimization problems. The goal of this exercise is to clearly identify and highlight the challenges encountered with the DE search while solving a range of optimization problems. We emphasize that understanding and resolving fundamental issues of a search procedure and considering the nature of the optimization problems at hand is the key to effective deployment of evolutionary procedures for search and optimization.
差异进化:性能和分析
在本文中,我们将差分进化(Differential Evolution, DE)算法与最近提出的约束处理策略相结合,并研究了结果算法在CEC'13测试套件[1]上的性能,以及其他约束优化问题。本练习的目标是在解决一系列优化问题时,清楚地识别和突出DE搜索遇到的挑战。我们强调,理解和解决搜索过程的基本问题,并考虑手头优化问题的性质是有效部署搜索和优化进化过程的关键。
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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