A Hybrid Flow Shop Scheduling Problem

dc.contributor.author Ayşegül Eda Özen
dc.contributor.author Gülce Çini
dc.contributor.author Merve Çamlıca
dc.contributor.author Nilay Çınar
dc.contributor.author Hasan Bahtiyar Soydan
dc.contributor.author Levent Kandiller
dc.contributor.author Hande Oztop
dc.contributor.author Çini, Gülce
dc.contributor.author Özen, Ayşegül Eda
dc.contributor.author Çamlıca, Merve
dc.contributor.author Kandiller, Levent
dc.contributor.author Öztop, Hande
dc.contributor.author Çınar, Nilay
dc.contributor.author Soydan, Hasan Bahtiyar
dc.contributor.editor N.M. Durakbasa , M.N. Osman Zahid , R. Abd. Aziz , A.R. Yusoff , N. Mat Yahya , F. Abdul Aziz , M. Yazid Abu , M.G. Gençyilmaz
dc.date.accessioned 2025-10-06T17:51:11Z
dc.date.issued 2020
dc.description.abstract Hybrid flow shop environment generally refers to the flow shop with multiple parallel machines per stage. Hybrid flow shop scheduling problem (HFSP) is a complex combinatorial optimization problem that came across in many real-life problems. In this study a real-life HFSP of a lubricant company is considered where the aim is to minimize total weighted completion time of the jobs. Apart from classical HFSPs the studied problem has additional constraints such as machine eligibility sequence-dependent setup times and machine capacities. Due to the additional constraints in the system a novel mixed integer linear programming model is proposed for the studied HFSP with three stages. As the problem is NP-hard two constructive heuristic algorithms and an improvement heuristic algorithm are also developed. The performance of the proposed heuristic algorithms is evaluated by comparisons with the optimal results obtained from the mathematical model. The extensive computational results show that proposed heuristic algorithms find near optimal results in reasonable computational times. Sensitivity analysis is also performed for the weight parameter of the problem which indicates that the proposed heuristic algorithms also perform very well for different weight parameter values. Finally the proposed heuristic algorithms are integrated into a user-friendly decision support system using Microsoft Excel VBA interface to provide an efficient scheduling tool for the company. © 2022 Elsevier B.V. All rights reserved.
dc.description.sponsorship This study is supported by TUBITAK (The Scientific and Technological Research Council of Turkey) under the program of “2209-B Undergraduate Research Projects for Industrial Applications Fellowship Program”. We would like to thank Deniz Türsel Eliiyi for her guidance and enlightenment. Additionally, we would like to thank İ. Çağcan Çatıkkaş and Alp Arslan for their support in this study. Finally, we are grateful to the company and Dilek Turan for their co-operation and support.
dc.description.sponsorship Türkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAK
dc.identifier.doi 10.1007/978-3-030-31343-2_55
dc.identifier.isbn 9789819650583, 9783031991585, 9783031948886, 9789819667314, 9789811937156, 9783030703318, 9789811622779, 9789811969447, 9789819701056, 9789819748051
dc.identifier.isbn 9789811509490
dc.identifier.isbn 9783030313425
dc.identifier.issn 21954364, 21954356
dc.identifier.issn 2195-4356
dc.identifier.scopus 2-s2.0-85076202827
dc.identifier.uri https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076202827&doi=10.1007%2F978-3-030-31343-2_55&partnerID=40&md5=2f43ce0b72e4ab7d8257a16c88c85422
dc.identifier.uri https://gcris.yasar.edu.tr/handle/123456789/9326
dc.identifier.uri https://doi.org/10.1007/978-3-030-31343-2_55
dc.language.iso English
dc.publisher Springer Science and Business Media Deutschland GmbH
dc.relation.ispartof 19th International Symposium for Production Research ISPR 2019
dc.rights info:eu-repo/semantics/closedAccess
dc.source Lecture Notes in Mechanical Engineering
dc.subject Heuristic Algorithm, Hybrid Flow Shop Scheduling, Machine Eligibility, Sequence-dependent Setup Times, Total Weighted Completion Time, Artificial Intelligence, Combinatorial Optimization, Constraint Programming, Decision Support Systems, Heuristic Algorithms, Machine Shop Practice, Scheduling, Sensitivity Analysis, Flow Shop Scheduling Problem, Heuristics Algorithm, Hybrid Flow Shop, Hybrid Flow Shop Scheduling, Machine Eligibility, Optimal Results, Sequence-dependent Setup Time, Total Weighted Completion Time, Weight Parameters, Integer Programming
dc.subject Artificial intelligence, Combinatorial optimization, Constraint programming, Decision support systems, Heuristic algorithms, Machine shop practice, Scheduling, Sensitivity analysis, Flow shop scheduling problem, Heuristics algorithm, Hybrid flow shop, Hybrid flow shop scheduling, Machine eligibility, Optimal results, Sequence-dependent setup time, Total weighted completion time, Weight parameters, Integer programming
dc.subject Heuristic Algorithm
dc.subject Sequence-Dependent Setup Times
dc.subject Hybrid Flow Shop Scheduling
dc.subject Machine Eligibility
dc.subject Total Weighted Completion Time
dc.title A Hybrid Flow Shop Scheduling Problem
dc.type Conference Object
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gdc.description.departmenttemp [Özen A.E.] Department of Industrial Engineering, Yaşar University, İzmir, Turkey; [Çini G.] Department of Industrial Engineering, Yaşar University, İzmir, Turkey; [Çamlıca M.] Department of Industrial Engineering, Yaşar University, İzmir, Turkey; [Çınar N.] Department of Industrial Engineering, Yaşar University, İzmir, Turkey; [Soydan H.B.] Department of Industrial Engineering, Yaşar University, İzmir, Turkey; [Kandiller L.] Department of Industrial Engineering, Yaşar University, İzmir, Turkey; [Öztop H.] Department of Industrial Engineering, Yaşar University, İzmir, Turkey
gdc.description.endpage 649
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
gdc.description.startpage 636
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gdc.virtual.author Öztop, Hande
gdc.virtual.author Kandiller, Levent
oaire.citation.endPage 649
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person.identifier.scopus-author-id Özen- Ayşegül Eda (57212215920), Çini- Gülce (57212207923), Çamlıca- Merve (57212210932), Çınar- Nilay (57212211943), Soydan- Hasan Bahtiyar (57212211081), Kandiller- Levent (6506822666), Oztop- Hande (57194232319)
project.funder.name This study is supported by TUBITAK (The Scientific and Technological Research Council of Turkey) under the program of “2209-B Undergraduate Research Projects for Industrial Applications Fellowship Program”. We would like to thank Deniz Türsel Eliiyi for her guidance and enlightenment. Additionally we would like to thank İ. Çağcan Çatıkkaş and Alp Arslan for their support in this study. Finally we are grateful to the company and Dilek Turan for their co-operation and support.
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