A rapid population-based iterated greedy for distributed blocking group flowshop scheduling with delivery time windows under multiple processing time scenarios

Abstract

This paper addresses the distributed blocking flowshop group scheduling problem (DBFGSP) in multi-line cell manufacturing, considering uncertain processing times and delivery time windows. A mathematical model with robust optimization objective was constructed, and its correctness is validated using the Gurobi solver. To enhance computational efficiency, two rapid evaluation methods and a modified idle time insertion method were designed. Building on these methods, a population-based iterated greedy algorithm, $RAP\_PIG\_ITI$, was proposed. The algorithm was tested against four metaheuristic algorithms on 810 instances, demonstrating its superior performance in robust objective and relative deviation index (RDI) metrics.