A Two-Tiered Destructive Iterated Greedy Approach for Enhancing Efficiency in Multi-Factory Hybrid Flow Shop Scheduling with Blocking Constraint

In the context of economic globalization, distributed manufacturing models are gradually emerging in large enterprises in order to provide faster demand response. In this paper, we study the distributed hybrid flow shop scheduling problem with blocking constraints (DBHFSP), whose optimization objective is makespan. A two-tiered destructive iterated greedy (tIG) algorithm is developed to optimize DBHFSP. First, the NEH2 heuristic is used to generate the initial solution; second, a cross-factory neighborhood structure is designed to coordinate the global search capability of the algorithm; to further explore the neighborhood space of the solution, we propose a permutation-based local strengthening strategy; finally, the simulated annealing (SA) method is used to augment the diversity of the algorithm. We conduct simulation experiments on 60 instances, and the experimental results prove that tIG outperforms other comparison algorithms.