Yavuz InceKorhan KarabulutM. Fatih TasgetirenQuanke Pan2025-10-062016978150900622910.1109/CEC.2016.7744220https://www.scopus.com/inward/record.uri?eid=2-s2.0-85008257490&doi=10.1109%2FCEC.2016.7744220&partnerID=40&md5=90bd5c6a911565881b4d5c1d425a5b9ehttps://gcris.yasar.edu.tr/handle/123456789/9752A discrete artificial bee colony (DABC) algorithm for the permutation flowshop scheduling problem with sequence-dependent setup times (PFSP-SDST) is presented in this paper. PFSP-SDST is an important problem that has practical applications in production facilities. The proposed DABC algorithm uses destruction and construction procedure to generate neighboring food sources. In addition a local search algorithm with insert and swap neighborhoods is used to enhance the solution quality. The main contribution of this work is providing a speedup algorithm for the swap neighborhood. Computational experiments are carried out to test the performance of the algorithm on a benchmark problem set from the literature. Experimental results show that the proposed DABC algorithm utilizing swap neighborhood is very competitive to the best performing algorithms from the literature. © 2017 Elsevier B.V. All rights reserved.EnglishArtificial Bee Colony Algorithm, Heuristic Optimization, Permutation Flowshop Problem, Sequence Dependent Setup Times, Swarm Intelligence, Benchmarking, Evolutionary Algorithms, Scheduling, Artificial Bee Colony Algorithms, Heuristic Optimization, Permutation Flow Shops, Sequence-dependent Setup Time, Swarm Intelligence, OptimizationBenchmarking, Evolutionary algorithms, Scheduling, Artificial bee colony algorithms, Heuristic optimization, Permutation flow shops, Sequence-dependent setup time, Swarm Intelligence, OptimizationConference Object