A Discrete Differential Evolution Algorithm for Multi-objective Scheduling in Blocking Flow Shop

This paper considers the problem of the multi-objective scheduling with makespan and total flow time minimizations for blocking flow shop.A multi-objective discrete differential evolution (MDDE) is proposed for searching alternative Pareto solutions,in which mutant individual is obtained by Pareto front solution or incumbent solution,and trial individual is generated by crossover operation while selection process is designed as a multi-objective selection strategy.Moreover,an insertion-based Pareto local search procedure is hybridized in this algorithm.The computational experiments on a bunch of instances for blocking flow shop show that the proposed algorithm can attain better non-dominated solution set in term of three performance measures,i.e.,Inverted Generational Distance,Set Coverage,and Hypervolume.