Optimimization of group scheduling using simulation with the meta-heuristic Extended Great Deluge (EGD) approach

Many companies apply cellular manufacturing systems (CMS) in order to improve production. One of the most significant problems encountered in production management is the scheduling problem, which has also been proven to be NP-hard. The objectives of the group scheduling problem in manufacturing are considered in order to minimize the makespan, the total flowtime and machine idletime. In this paper, we propose an approach for optimizing the scheduling of the manufacturing tasks of all parts of a product family, including exceptional elements. To solve this problem, an Extended Great Deluge (EGD) approach algorithm is applied in order to determine the optimal sequence of parts in each cell, minimizing the makespan and the total flowtime; following that, a heuristic method is applied to introduce exceptional elements. The results of the proposed hybrid approach show a major improvement when compared with those obtained using one of the best algorithms that has so far been presented by other researchers.