A Meta-Heuristic Algorithm for Flexible Flow Shop Sequence Dependent Group Scheduling Problem

In this research, the flexible flow shop sequence dependent group scheduling problem (FFSDGS) with minimization of makespan as the criterion (FFm|fmls, Ssd|Cmax) is investigated. Since the problem is shown to be NP-hard, meta-heuristic algorithms are required to efficiently solve industry size problems. Thus, six different meta-heuristic algorithms based on tabu search (TS) are developed to efficiently solve for near optimal solutions of the proposed problem. By using randomized complete block design and considering the objective function value of each algorithm as the criterion, the best algorithm among the proposed ones is identified. The experiments are performed by solving the available test problems in the literature. Then, the performance of the best developed meta-heuristic algorithm is compared with the existing algorithm in the literature. A comparison based on paired t-test shows that the average makespan of the proposed algorithm in this research is better than the average makepan of the existing algorithm in the literature. In particular, defining the neighborhoods to allow for the possibility of processing the same group on more than one machine, when multiple machines are available for a stage, contributed to identifying better quality solutions than have been identified in the past. In other words, this research investigates into the possibility of moving away from defining the neighborhoods for groups in a traditional sense where a group is assigned to only one machine in a stage to more than one machine.