Abstract: Flexible Job Shop Scheduling Problem (FJSP) is an important extension of the classic job shop scheduling problem where each operation can be handled on multiple machines and vice versa. Combined with the actual production process of processing time, machine load, operating costs and other conditions, a multi-objective scheduling model is established. Aiming at the defect of insufficient convergence of NSGA2 algorithm, the immune balance principle is introduced to improve the selection strategy and elite retention strategy of NSGA2 algorithm, avoiding the local convergence problem and improving the optimization performance of the algorithm. By comparing with heuristic rules and various intelligent algorithms, the improved NASA2 algorithm can get a better solution. Using improved NAGA2 algorithm to solve the case not only effectively overcomes the barriers in order of magnitude and dimension of the objectives, but also obtains a satisfactory pareto solution set, further verifying the feasibility of the algorithm and the model.

Key words: flexible job shop manufacturing, multi-objective scheduling model, immune balance, selection strategy, elite retention strategy