关键词: 柔性作业车间调度, 最小机器数, 遗传算法, 双层优化, 大变异策略

Abstract: Aiming at the flexible job shop scheduling problem that expects to complete production with the minimum number of machines, a bi-level optimization model is established that minimizes the makespan as the inner goal and the minimum number of machines as the outer goal. That is, under the conditions of meeting the due date and minimizing the makespan, it tries to reduce the number of machines to find the minimum number of machines for workshop scheduling. According to the characteristics of the model and algorithm, a genetic algorithm based on the great mutation strategy is designed. The algorithm uses two-dimensional chromosome coding, sequence selection strategy, and uses the priority operation crossover operator and the great mutation strategy to ensure the diversity of the population. After verification and analysis of examples, the model is established and is better than the scheduling model of the specified number of machines, which can save manpower and processing costs for the enterprise and improve the utilization rate of machines. Compared with the other five algorithms, it can be seen that the algorithm is effective and can achieve better optimization goals.

Key words: flexible job shop scheduling, minimum number of machines, genetic algorithm, bi-level optimization, great mutation strategy