Considering the deterioration of equipment in the actual production process,aiming at the flexible job shop scheduling issue in which the actual processing time is composed of basic processing time and variable penalty time,a multi-objective scheduling optimization model is constructed to minimize the completion time,total energy consumption and total machine load,and an improved non-dominated sorting genetic algorithm is proposed to solve the problem.Combined with the characteristics of the problem,a parallel double-layer coding method based on process and machine and a greedy insertion decoding method considering machine deterioration effect are designed in this algorithm;By introducing Pareto level into crossover and mutation operators,and a strategy based on dynamic control of crossover and mutation parameters is designed to enhance the optimization efficiency of the algorithm;In order to increase population diversity and strengthen the local search ability of the algorithm,a hierarchical elite retention strategy and four neighborhood search mechanisms are designed respectively.Finally,the feasibility of the established model and the effectiveness of the improved algorithm are proved by specific examples.
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