Minimizing makespan in a Flow Shop Sequence Dependent Group Scheduling problem with blocking constraint

Abstract Flow Shop Sequence Dependent Group Scheduling (FSDGS) problems gathered much attention from the body of literature in recent years. Nevertheless, the combination of blocking constraint and Group Technology (GT) principles has not been faced by academics so far. The aim of the present paper is to propose an original meta-heuristic approach for minimizing makespan in a FSDGS problem with blocking constraint. To this end, a novel Parallel Self-Adaptive Genetic Algorithm (PSAGA) which adaptively varies the genetic parameters along the evolutionary mechanism was devised. Validation of the proposed metaheuristics was performed by means of the global optima generated by a proper mixed integer linear programming model. An extended experimental campaign, also supported by a specific statistical analysis, demonstrates the effectiveness of the proposed approach compared to other meta-heuristics arising from the relevant literature.