Minimizing Makespan in Distributed Blocking Flowshops Using Hybrid Iterated Greedy Algorithms

This paper studies the distributed blocking flow shop scheduling problem (DBFSP) using meta-heuristics. A mixed integer programming model for solving the problem is proposed, and then three versions of the hybrid iterated greedy algorithm (HIG(1), HIG(2), and HIG(3)) 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 HIG(1), HIG(2), and HIG(3) 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 HIG(1) is the most effective.