Ying-Ying HuangQuan-ke PanXiaoLu HuMehmet Fatih TasgetirenJiang-ping HuangTasgetiren, M. FatihHuang, Ying-YingPan, Quan-keHu, XiaoLuHuang, Jiang-pingJ FuJ Sun2025-10-062020978-988-15639-0-397898815639032161-29271934-176810.23919/CCC50068.2020.91886832-s2.0-85091398703https://gcris.yasar.edu.tr/handle/123456789/7056https://doi.org/10.23919/CCC50068.2020.9188683Nowadays the distributed assembly permutation flowshop problem (DAPFSP) has important applications in practice. In this paper we propose a group iterated local search (gILS) algorithm to solve the problem with total flowtime (TF) criterion. We use the heuristic method based on a ascending order which is originated from the NEH. In order to simplify and optimize the algorithm we introduce two kinds of local search methods based on products and jobs respectively. In addition considering the diversity of search area we propose a probabilistic random selection based on the TF value and the number of iterations to determine the optimized solution. Acceptance criterion is a simple comparison to determine whether a new solution is acceptable or not. Finally we calculate 180 instances with our proposed algorithm and compare the results with those from the recent effective algorithms. The results verify the superiority of the presented gILS algorithm.Englishinfo:eu-repo/semantics/closedAccessDistributed flowshop scheduling, Assembly line scheduling, Iterated local search, Total flowtimeSEQUENCE-DEPENDENT SETUP, SCHEDULING PROBLEM, GENETIC ALGORITHMDistributed Flowshop SchedulingTotal FlowtimeAssembly Line SchedulingIterated Local SearchConference Object