This paper investigates how often the popular configurations of Differential Evolution generate solutions outside the feasible domain. Following previous publications in the field, we argue that what the algorithm does with such solutions and how often this has to happen is important for the overall performance of the algorithm and interpretation of results. Based on observations therein, we conclude that significantly more solutions than what is usually assumed by practitioners need to undergo some sort of 'correction' to conform with the definition of the problem's search domain. A wide range of popular Differential Evolution configurations is considered in this study. Conclusions are made regarding the effect the Differential Evolution components and parameter settings have on the distribution of proportions of infeasible solutions generated in a series of independent runs. Results shown in this study suggest strong dependencies between proportions of generated infeasible solutions and every aspect mentioned above. Further investigation of the distribution of proportions of generated infeasible solutions is required.
翻译:本文探讨不同进化的流行配置在可行领域之外产生解决办法的频率。 此前的实地出版物指出,算法对此类解决办法的作用以及这种作用的发生频率对于算法和结果解释的整体性表现很重要。 根据其中的观察,我们的结论是,比从业人员通常认为的要多得多的解决方案需要经过某种“ 校正” 才能与问题搜索领域的定义保持一致。本研究报告考虑了广泛的各种流行差异进化配置。 有关不同进化组成部分和参数设置对一系列独立运行中产生的不可行解决办法分布比例的影响的结论。 本研究的结果表明,产生不可行解决办法的比例与上述所有方面之间有着很强的相互依赖性。 需要进一步调查产生不可行解决办法的比例分布情况。