Development of an Integrated GA and PSO Scheduling Method Considering the Skill Level of the Workers

In make-to-order plants that produce a wide variety of products in small lots, the production lead time must be reduced to meet the due date specified by the customer. In this study, we propose an integrated scheduling method in which GA and local search methods are used to allocate the work of jobs to machines to obtain the best chromosomes. PSO is used to assign works of jobs to the workers. The production scheduling problem is challenging to find optimal solutions because of the large number of valuables. PSO is one of the effective methods in the meta-heuristics method for the reduction of computation time. Therefore, this study attempts to develop PSO and GA. PSO is used to seek the worker’s assignment, and GA is used to seek the job assignment. The performance of the proposed method is investigated using some scheduling models.