An ensemble discrete differential evolution for the distributed blocking flowshop scheduling with minimizing makespan criterion
作者：
Highlights：
• An ensemble discrete differential evolution (EDE) algorithm is proposed.
• Two different heuristic methods and one random strategy are introduced into EDE.
• The mutation, crossover and selection operators are redesigned to assist the EDE algorithm.
• An elitist retain strategy is introduced into the framework of EDE algorithm.
• The parameters of the EDE algorithm are calibrated by the design of experiments (DOE) method.
摘要
•An ensemble discrete differential evolution (EDE) algorithm is proposed.•Two different heuristic methods and one random strategy are introduced into EDE.•The mutation, crossover and selection operators are redesigned to assist the EDE algorithm.•An elitist retain strategy is introduced into the framework of EDE algorithm.•The parameters of the EDE algorithm are calibrated by the design of experiments (DOE) method.
论文关键词：Distributed blocking flowshop,Discrete differential evolution,Heuristics method,Front delay,Elitist retain strategy
论文评审过程：Received 15 November 2019, Revised 17 June 2020, Accepted 17 June 2020, Available online 3 July 2020, Version of Record 21 July 2020.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.113678
