A Heuristic Approach on Flexible Job-Shop Scheduling Problem with Maintenance Activities by Considering Weight of the Jobs

Most of the researchers studying scheduling problems assume that machines are available all the time and, maintenance and setup times are usually neglected. In real-life production environment, however, this assumption is not valid. In fact, in real-life production environment, machines are periodically and/or non-periodically unavailable. In this thesis, flexible job shop scheduling problem with maintenance activities is examined. Maintenance activities are considered as non-periodical and they are occurring related to weight of the jobs processed by the machine. Weight of any job is independent from its processing time. There is no relationship between the weight and the processing time of jobs. A heuristic approach based on particle swarm optimization is presented to solve this variant of flexible job-shop scheduling problem. The presented algorithm is tested on some representative problems and the results prove that presented algorithm is a alternative and effective approach for the problem.