Bi-objective no-wait multiproduct multistage product scheduling problem with flexible due dates based on MOIDE- MA

Abstract

This paper deals with the no-wait multiproduct multistage product scheduling problem (NWMMSP) with minimum makespan and maximum mean customer’s satisfaction level criteria. The mean customer’s satisfaction level criterion related to flexible due date is introduced to approach an imprecise or flexible nature of the data in a practical manufacturing environment. A novel discrete multi-objective evolutionary algorithm combined with an improved differential evolution algorithm and memetic algorithm (MOIDE-MA) is proposed to solve the multi-objective NWMMSP. The improved discrete differential evolution algorithm (IDE) mainly focuses on the edge area of the Pareto front (PF) space and the single objective guide strategy to construct better reference points. Meanwhile, an information-sharing strategy is introduced in IDE to improve the information diversity and enhance the search capabilities for the whole PF. A novel memetic algorithm (MA) based on genetic algorithm (GA) and local search related to the researched scheduling problem is developed to improve the distribution uniformity and accuracy of the non-dominated solutions obtained by IDE further. IDE gains some useful information extracted from the external archive of MA to speed up its search. Computational and simulation results show that the improvement strategy proposed in the algorithm can effectively improve the performance of MOIDE-MA. Furthermore, the proposed algorithm is compared with three other multi-objective scheduling optimization approaches based on different scale multi-objective NWMMSP instances. The experimental results show the effectiveness of the proposed MOIDE-MA.