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
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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