Splitting the fitness and penalty factor for temporal diversity increase in practical problem solving

作者:

Highlights:

• The theory-inspired proposition of objective and penalty functions split.

• Flow optimization in computer performed by a problem-dedicated method.

• Diversity increase by automatic and dynamic management of the penalty factor.

摘要

•The theory-inspired proposition of objective and penalty functions split.•Flow optimization in computer performed by a problem-dedicated method.•Diversity increase by automatic and dynamic management of the penalty factor.

论文关键词:Penalty factor separation,Diversity preservation,Evolutionary computation,Dynamic subpopulation number control,Messy-coding,Genetic algorithm

论文评审过程:Received 13 March 2019, Revised 15 November 2019, Accepted 8 December 2019, Available online 13 December 2019, Version of Record 20 December 2019.

论文官网地址:https://doi.org/10.1016/j.eswa.2019.113126