Differential Evolution and Engineering Problems

Mendel Pub Date : 2023-06-30 DOI:10.13164/mendel.2023.1.045
P. Bujok, M. Lacko, Patrik Kolenovsky
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引用次数: 2

Abstract

In this paper, the performance of the Differential Evolution algorithm is evaluated when solving real-world problems. A Set of 13 engineering optimisation problems was selected from the fields of mechanics and industry to illustrate the usability of the Differential Evolution algorithm. Twelve variants of the standard Differential Evolution with various settings of the control parameters are compared with 19 state-of-the-art adaptive variants of this algorithm. The results are analysed statistically to achieve significant differences. Three variants of adaptive Differential Evolution provided better results compared to other algorithms. Some adaptive variants of Differential Evolution perform significantly worse than the original Differential Evolution with the fixed setting of the control parameters.
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差分进化与工程问题
本文对差分进化算法在解决实际问题时的性能进行了评价。从力学和工业领域中选择了13个工程优化问题来说明微分进化算法的可用性。将具有不同控制参数设置的标准微分进化的12种变体与该算法的19种最先进的自适应变体进行了比较。对结果进行统计分析,得出显著差异。与其他算法相比,自适应差分进化的三个变体提供了更好的结果。在控制参数固定的情况下,微分进化的一些自适应变体的性能明显不如原始的微分进化。
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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来源期刊
Mendel
Mendel Decision Sciences-Decision Sciences (miscellaneous)
CiteScore
2.20
自引率
0.00%
发文量
7
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