Enhanced migrating birds optimization algorithm for the permutation flow shop problem with sequence dependent setup times

•We solve the permutation flowshop problem with sequence-dependent setup times to minimize the makespan.•We propose an adapted heuristic which outperforms references heuristics.•We propose an enhanced migrating birds optimization algorithm.•The presented algorithm used several new introduced mechanisms.•The presented algorithm tested against 5 algorithms. State-of-the-art results. The original approach outperforms.

This paper presents an enhanced migrating bird optimization (MBO) algorithm and a new heuristic for solving a scheduling problem. The proposed approaches are applied to a permutation flowshop with sequence dependent setup times and the objective of minimizing the makespan. In order to augment the MBOs intensification capacity, an original problem specific heuristic is introduced. An adapted neighborhood, a tabu list, a restart mechanism and an original process for selecting a new leader also improved the MBO's behavior. Using benchmarks from the literature, the resulting enhanced MBO (EMBO) gives state-of-the-art results when compared with other algorithms reference. A statistical analysis of the numerical experiments confirms the relative efficiency and effectiveness of both EMBO and the new heuristic.