AN EFFICIENT METHOD OF JOB-SHOP SCHEDULING BASED ON SIMULATED ANNEALING

抄録

Transition from low-mix high volume manufacturing to high-mix low-volume manufacturing has increased importance of job-shop scheduling. Because of non-deterministic polynomial time hardness of job-shop scheduling problem (JSP), approximate optimization based on meta-heuristics have been actively discussed, and methods using simulated annealing (SA) have been proposed. Because SA has a disadvantage that good solutions cannot be obtained efficiently if the initial solution is not given appropriately, methods for solving this problem have been proposed for JSPs aiming at minimizing makespan. In high-mix low-volume manufacturing, it is important to minimize lead times in addition to makespan. This research deals with development of an efficient method using SA for JSPs aiming at minimizing average lead time (ALT). Methods of neighborhood limitation in SA for reducing ALT were developed by focusing on waiting time of operations. It was proven that using the proposed methods in SA with appropriate probability is effective by numerical examples.