Multi-objective flexible job-shop scheduling problem researching based on improved adaptive NSGA-II

Abstract

To solve the scheduling problem of products manufacturing in the military electronic equipment enterprises, a multi-objective flexible job-shop scheduling model was established with the objective of minimum the make span, production costs and equipment load. According to the characteristics of flexible job-shop scheduling problem, an adaptive NSGA-II algorithm was proposed in this paper, which could change the probabilities of crossover and mutation operation at different stages of genetic processes. To improve the diversity of population, the algorithm performed independent crossover and mutation operations on the working processes and equipment. Besides, a population independent elite retention strategy was adopted to avoid the loss of optimum solutions. At last, the feasibility and validity of the improved adaptive NSGA-II are verified by a flexible job-shop example.