A Comprehensive Analysis of Differential Evolution in Single-Objective Optimization

机译：单目标优化中差异演化的综合分析

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摘要

We perform a comprehensive analysis of Differential Evolution (DE) optimization strategies, in comparison to Genetic Algorithms (GAs). A number of diversified benchmark problems of interest have been considered for single-objective (SO) optimization. We investigate the algorithms' behaviour and performance with respect to their parameters' setting. We measure the performance in terms of reliability, accuracy and convergence speed.

机译：与遗传算法（GA）相比，我们对差异进化（DE）优化策略进行了全面分析。对于单目标（SO）优化，已经考虑了许多感兴趣的基准基准问题。我们针对算法的参数设置来研究算法的行为和性能。我们根据可靠性，准确性和收敛速度来衡量性能。

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来源
《Proceedings of the 7th international conference on "mathematical methods in reliability": theory, methods, applications.》|2011年|p.914-921|共8页
会议地点 Beijing(CN);Beijing(CN)
作者
ENRICO ZIO; GIORGIO VIADANA;
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作者单位

Chair at the European Foundation for New Energy, EDF at Ecole Centrale Paris-Supelec, Paris, France;

Politecnico di Milano, Energy Department, Milano, 20133, Italy;

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中图分类可靠性理论;可靠性理论;
关键词
Evolutionary Algorithm; Differential Evolution; Genetic Algorithm; Single-Objective optimization;

机译：进化算法；差分进化；遗传算法；单目标优化;

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A Comprehensive Analysis of Differential Evolution in Single-Objective Optimization

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