Hybrid multiobjective evolutionary algorithm based on differential evolution for flow shop scheduling problems

•Detecting location of individual in Pareto front by fitness function in HMOEA.•Converging to the multi-area of Pareto front by elitist and selection strategies.•DE enhances the local search on elitist derived from HMOEA.•Two DE mutation operators are designed for the individuals in elite population.•Numerical comparisons indicate efficacy of HMOEA/DE on benchmark and FSP.