Supply chain-oriented two-stage assembly flowshops with sequence-dependent setup times

Abstract

Supply chain-oriented scheduling problems have received recent recognition among production research scholars due to their ability in integrating production planning and control across manufacturing systems. This study contributes to the literature of the distributed scheduling problems developing an original Mixed-Integer Linear Programming (MILP) formulation to the Distributed Two-Stage Assembly Flowshop Scheduling Problem with Sequence-Dependent Setup Times (DTSAFSP-SDSTs). Besides, the Iterated Greedy algorithm is extended to effectively solve this relatively complex production scheduling situation considering the makespan as the optimization criterion. Extensive numerical tests and statistical analyses are conducted to evaluate the effectiveness of the developed solution algorithm. Results showed that the Improved Iterated Greedy (IIG) algorithm yields the best solution in nearly all of the large-scale instances. The statistical test of significance confirmed that IIG is superior to the current-best-performing algorithm. This study contributes to the transition from standalone optimization to integrated production planning and control of distributed manufacturing systems.