M. Fatih TasgetirenHande OztopQuanke PanMustafa Arslan OrnekTalya TemizceriTasgetiren, M. FatihTemizceri, TalyaOztop, HandePan, Quan-KeOrnek, M. Arslan2025-10-0620219783031963100, 9783642034510, 9783540768029, 9783642364051, 9783031852510, 9783540959717, 9783031534447, 9783642054402, 9783642327254, 97830309490991860949X, 1860950310.1007/978-3-030-58930-1_32-s2.0-85097956206https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097956206&doi=10.1007%2F978-3-030-58930-1_3&partnerID=40&md5=3d50db83c04a56709c58a6dd8fb853a4https://gcris.yasar.edu.tr/handle/123456789/9097https://doi.org/10.1007/978-3-030-58930-1_3Permutation flow shop scheduling problem is a well-known problem in the scheduling literature. Even though various multi-objective permutation flowshop scheduling problems have been studied in the literature energy consumption consideration in scheduling is still very seldom. In this paper we consider a bi-objective permutation flowshop scheduling problem with the objectives of minimizing the total energy consumption and the makespan. We present a bi-objective mixed integer programming model for the problem applying a speed-scaling approach. Then we employ the augmented ε -constraint method to generate the Pareto-optimal solution sets for small-sized instances. For larger instances we use the augmented ε -constraint method with a time limit on CPLEX solver to approximate the Pareto frontiers. We also propose a heuristic approach which employs a very recent variable block insertion heuristic algorithm. In order to evaluate performance of the proposed algorithm we have carried out detailed computational experiments using well-known benchmarks from the literature. First we present the performance of the proposed algorithm on small-sized problems, then we show that the proposed algorithm is very effective to solve larger problems as compared with the time-limited CPLEX. © 2020 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessBook Part