New Benchmark Algorithm for Minimizing Total Completion Time in blocking flowshops with sequence-dependent setup times

Abstract

Abstract Just-in-time production in large enterprises along with the factory’s limited space highlights the need for scheduling tools that consider blocking conditions. This study contributes to the scheduling literature by developing an effective metaheuristic to address the Blocking Flowshop Scheduling Problems with Sequence-Dependent Setup-Times (BFSP with SDSTs). Including a new constructive heuristic and a local search mechanism customized for the blocking and setup time features, the Extended Iterated Greedy (EIG) algorithm effectively solves this highly intractable scheduling extension. The performance of the EIG algorithm is compared with that of the best-performing algorithms in the literature developed to solve the BFSP with SDSTs. Extensive numerical tests and statistical analyses verify EIG’s superiority over the benchmark algorithms and show that EIG performs steadily over various operational situations. Applications of the improved Iterated Greedy in this study are worthwhile topics to solve other complex scheduling problems.