关键词: 柔性作业车间, 调度, 多目标优化, 批量分割, 粒子群算法

Abstract: To solve the problem of multi-objective flexible Job Shop scheduling with lot-splitting, a novel multi-objective flexible size lot-splitting scheduling algorithm based on particle swarm optimization algorithm was proposed. In this algorithm, a flexible size lot-splitting approach based on “cursors” was put forward. Combined the lot-splitting with the sub-lot scheduling, a novel particle coding scheme was proposed. As a result, the algorithm could not only split lots into flexible size sub-lots according to machine workloads, but also optimize the sub-lots routing and sequencing simultaneously. The preference information of decision maker was incorporated in the algorithm and was used to guide the search direction of the algorithm. And the search results were concentrated in preferred region of the Pareto front and the difficulty in selecting a satisfying solution from numerous non-inferior solutions was eliminated. Performance of the proposed algorithm was evaluated through simulations, and the results demonstrated the feasibility and efficiency of the proposed algorithm. Finally, an example from the practical production was addressed. Experimental results could provide reference for production practice.

Key words: flexible Job Shop, scheduling, multi-objective optimization, lot-splitting, particle swarm optimization algorithm, preference information