Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.13091/1647
Title: | Artificial bee colony algorithm for solving multi-objective distributed fuzzy permutation flow shop problem | Authors: | Baysal, Mehmet Emin Sarucan, Ahmet Büyüközkan, Kadir Engin, Orhan |
Keywords: | agreement index artificial bee colony Distributed fuzzy permutation flow-shop fuzzy completion time multi-objective Fuzzy sets Machine shop practice Scheduling Agreement index Algorithm for solving Bee colony algorithms Distributed fuzzy permutation flow-shop Flow shop problems Flow shop scheduling problem Fuzzy completion time Multi objective Permutation flow-shop scheduling Permutation flowshops Optimization |
Issue Date: | 2022 | Publisher: | IOS Press BV | Abstract: | The distributed permutation flow shop scheduling (DPFSS) is a permutation flow shop scheduling problem including the multi-factory environment. The processing times of the jobs in a real life scheduling problem cannot be precisely know because of the human factor. In this study, the process times and due dates of the jobs are considered triangular and trapezoidal fuzzy numbers for DPFSS environment. An artificial bee colony (ABC) algorithm is developed to solve the multi-objective distributed fuzzy permutation flow shop (DFPFS) problem. First, the proposed ABC algorithm is calibrated with the well-known DPFSS instances in the literature. Then, the DPFSS instances are fuzzified and solved with the algorithm. According to the results, the proposed ABC algorithm performs well to solve the DFPFS problems. © 2022 - IOS Press. All rights reserved. | URI: | https://doi.org/10.3233/JIFS-2191202 https://hdl.handle.net/20.500.13091/1647 |
ISSN: | 10641246 |
Appears in Collections: | Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections |
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