Abstract: Distributed manufacturing(DM) becomes one of the mainstream manufacturing models, which widely exists in real-world production, including aviation, electronics industries and etc. In DM, there are differences in the number of machines, machine processes, and raw material transportation conditions in every factory, that is, heterogeneity. However, there is no research considering the heterogeneity of factories in the known distributed scheduling literature. Based on this, a multi-objective distributed heterogeneous no-wait flowshop scheduling problem with sequence-dependent setup time(MDHNWFSP-SDST) has been studied. A multi-objective optimization model is established with the objectives of makespan and total tardiness. Based on the MDHNWFSP-SDST feature, a multi-objective discrete artificial bee colony(MODABC) based on pareto optimality is proposed. In MODABC, an improved PWQ heuristic(IPWQ) is designed to initialize the population. IPWQ solves the problems of an order of magnitude and duplicate solutions in PWQ. In the employed bee phase, four neighborhood structures are applied to generate feasible solutions to improve the quality of population. In the onlooker phase, an improved position-based crossover is designed. The superior characteristics of the parents can be retained and the population diversity can be maintained. In the scout phase, a multi-objective local search is embedded to ensure sufficient search of the solution space. Finally, by comparing with other effective multi-objective optimization algorithms, the effectiveness and superiority of the proposed MODABC have been verified.

Key words: distributed no-wait flowshop scheduling, artificial bee colony, heterogeneous, multi-objective optimization