关键词: 差分进化算法, 多目标优化, 局部搜索, 柔性作业车间, 批量调度

Abstract: By considering the scheduling objectives such as makespan,product cost and equipment utilization,a multi-objective flexible Job-Shop scheduling model of batch production was described.To solve batch partition and batch scheduling,a multi-objective batch scheduling algorithm based on differential evolution was proposed by using encoding mode of combining batch splitting chromosome with batch scheduling chromosome.A Pareto-based ranking and crowding distance strategy were introduced to select the next population,and an external archive was employed to hold and update the non-dominated solutions.To balance global exploration and local exploitation,a multi-objective local searching strategy combining dynamic random search with random mutation based on critical path was designed.Through scheduling examples and practical dye vat scheduling,the proposed algorithm could reduce the makespan effectively,and obtain more evenly distributed Pareto non-dominate solutions.

Key words: differential evolution algorithm, multi-objective optimization, local search, flexible Job Shop, batch scheduling