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Title: | Solution method for a large-scale loom scheduling problem with machine eligibility and splitting property |
Authors: | Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü. Eroǧlu, Duygu Yılmaz Özmutlu, Hüseyin Cenk ABH-5209-2020 AAH-1079-2021 56120864000 6603061328 |
Keywords: | Materials science Genetic algorithms Large-scale problem Loom Scheduling Sequence-dependent setup Genetic-algorithm Parallel machines Programming approach Minimizing makespan Times Jobs Restrictions Constraints Algorithms Chromosomes Looms Problem solving Genetic algorithms Optimization Textile industry Chromosome structure Hybrid genetic algorithms Large-scale problem Machine eligibility Machine eligibility constraint Scheduling problem Sequence-dependent setup time Unrelated parallel machines Job shop scheduling |
Issue Date: | 3-Apr-2017 |
Publisher: | Taylor & Francis |
Citation: | Eroğlu, D. Y. ve Özmutlu, H. C. (2017). ''Solution method for a large-scale loom scheduling problem with machine eligibility and splitting property''. Journal of the Textile Institute, 108(12), 2154-2165. |
Abstract: | In this paper, we focused on a real-life, large-scale problem of loom scheduling, which has 1100 independent jobs and 133 unrelated parallel machines with machine eligibility constraint. The authors focused on the scheduling problems that includes sequence-dependent setup times and the job splitting property to minimize the makespan. An adapted version of hybrid genetic algorithm in this study, incorporated a machine eligibility constraint. Adding this constraint complicated the problem, but doing so is compulsory to solve a real-life problem. To simplify the problem, we used the typesetting structure of the weaving industry. Utilizing random key numbers provided feasible chromosomes for each generation. Flexible chromosome structures and local search adaptation into the genetic algorithm were some of the other factors that allowed us to improve the makespan by up to 14% in this application. |
URI: | https://doi.org/10.1080/00405000.2017.1316177 https://www.tandfonline.com/doi/full/10.1080/00405000.2017.1316177 1754-2340 http://hdl.handle.net/11452/30981 |
ISSN: | 0040-5000 |
Appears in Collections: | Scopus Web of Science |
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