A collaboration-based multi-objective algorithm for distributed hybrid flowshop scheduling with resource constraints

Abstract

With the development of the realistic manufacturing process, the distributed scheduling, machine velocity, and resource constraints have attracted much attention. This paper addresses the distributed hybrid flowshop scheduling problem (DHFSP) with machine velocity and resource constraints to minimize the makespan and total energy consumption simultaneously. A mathematical model of the problem is formulated. To solve the proposed problem, a collaboration-based multi-objective algorithm (CBMA) is developed. First, a machine velocity adjustment rule considering resource constraints is proposed by analyzing the characteristics of the problem. In the proposed algorithm, each solution is represented by a well-designed three-dimensional vector. Then, an objective-balanced machine selection strategy is employed to balance the quality and diversity of the initial population. Next, a Pareto knowledge-based collaborative search mechanism enhances the global search ability in each iteration. To improve the convergence of the algorithm, a distributed machine velocity adjustment rule is embedded into the local search. Finally, a set of instances based on realistic industrial processes are tested. The effective performance of the proposed algorithm is verified through computational comparisons.