Differential evolution outside the box

This paper investigates how often the popular configurations of Differential Evolution gen-erate 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 hap-pen 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 distribu-tion of proportions of infeasible solutions generated in a series of independent runs. Results shown in this study suggest strong dependencies between proportions of generated infea-sible solutions and every aspect mentioned above. Further investigation of the distribution of proportions of generated infeasible solutions is required. (c) 2021 Elsevier Inc. All rights reserved.

Automated summary

This study examines how often popular configurations of Differential Evolution generate solutions outside the feasible domain, emphasizing the importance of correcting these solutions to conform with the problem's search domain definition. The research concludes that Differential Evolution components and parameter settings strongly influence the distribution of proportions of infeasible solutions generated. Further investigation into the distribution of proportions of generated infeasible solutions is needed.