A Hybrid Flow Shop Scheduling Problem
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Date
2020
Authors
Ayşegül Eda Özen
Gülce Çini
Merve Çamlıca
Nilay Çınar
Hasan Bahtiyar Soydan
Levent Kandiller
Hande Oztop
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Science and Business Media Deutschland GmbH
Open Access Color
Green Open Access
No
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
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.
Description
Keywords
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, 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, Heuristic Algorithm, Sequence-Dependent Setup Times, Hybrid Flow Shop Scheduling, Machine Eligibility, Total Weighted Completion Time
Fields of Science
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OpenCitations Citation Count
N/A
Source
19th International Symposium for Production Research ISPR 2019
Volume
Issue
Start Page
636
End Page
649
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Scopus : 0
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Mendeley Readers : 33
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