Distributed Permutation Flow Shop Scheduling Method Based on Efficient Job Allocation Strategy.

Distributed manufacturing can effectively improve production efficiency and shorten delivery cycle, which is one of the current research hotspots. Distributed permutation flow shop scheduling problem is a classical NP-hard problem, which includes two parts: job allocation and job ordering. However, most current researches focus on job ordering, which leads to local optimal solutions. Therefore, This paper proposes a distributed permutation flow shop scheduling method based on efficient job allocation. First, this paper studies the two sub-problems of the job allocation problem respectively, proposes the corresponding fast estimation method and proves it by experiments. Second, according to the characteristics of distributed permutation flow shop, the corresponding specialized efficient scheduling algorithm is proposed. Finally, 90 cases on the famous TA benchmark were selected for experiments. The experimental results showed that the proposed algorithm obtained 79 optimal solutions, and the coverage rate of the optimal solution reached 87.8%, which verified the effectiveness of the algorithm.