Yingying HuangQuanke PanXiaolu HuM. Fatih TasgetirenJiangping HuangJ. Fu , J. Sun2025-10-0620209789881563941, 9789887581581, 9789887581536, 9789881563804, 9789881563910, 9789881563842, 9789881563972, 9789881563811, 9789881563835, 978988758154321612927, 1934176810.23919/CCC50068.2020.9188683https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091398703&doi=10.23919%2FCCC50068.2020.9188683&partnerID=40&md5=4639b84670a310689fd0317c031e4127https://gcris.yasar.edu.tr/handle/123456789/9190Nowadays 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. © 2020 Elsevier B.V. All rights reserved.EnglishAssembly Line Scheduling, Distributed Flowshop Scheduling, Iterated Local Search, Total Flowtime, Local Search (optimization), Acceptance Criteria, Effective Algorithms, Iterated Local Search, Local Search Method, Number Of Iterations, Optimized Solutions, Permutation Flow Shops, Random Selection, Heuristic MethodsLocal search (optimization), Acceptance criteria, Effective algorithms, Iterated local search, Local search method, Number of iterations, Optimized solutions, Permutation flow shops, Random selection, Heuristic methodsConference Object