Minimizing Makespan in Distributed Blocking Flowshops Using Hybrid Iterated Greedy Algorithms

This paper studies the distributed blocking flow shop scheduling problem (DBFSP) using metaheuristics. A mixed integer programming model for solving the problem is proposed, and then three versions of the hybrid iterated greedy algorithm (HIG₁, HIG₂, and HIG₃) are developed, combining the advantages of an iterated greedy algorithm with the operators of the variable Tabu list, the constant Tabu list, and the cooling schedule. A benchmark problem set is used to assess empirically the performance of the HIG₁, HIG₂, and HIG₃ algorithms. Computational results show that all the three versions of the proposed algorithm can efficiently and effectively minimize the maximum completion time among all factories of the DBFSP, and HIG₁ is the most effective.