Product processing prioritization in hybrid flow shop systems supported on Nash bargaining model and simulation-optimization
•Proposing a game-based simulation–optimization approach in HFS scheduling.•Using bargaining approach to determine the optimal priority processing rule in HFS.•Using scheduling game in an HFS exposed to the stochastic failure of machinery.•The efficiency of the approach due to the significant reduct...
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| Published in | Expert systems with applications Vol. 180; p. 115066 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Elsevier Ltd
15.10.2021
Elsevier BV |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0957-4174 1873-6793 |
| DOI | 10.1016/j.eswa.2021.115066 |
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| Abstract | •Proposing a game-based simulation–optimization approach in HFS scheduling.•Using bargaining approach to determine the optimal priority processing rule in HFS.•Using scheduling game in an HFS exposed to the stochastic failure of machinery.•The efficiency of the approach due to the significant reduction of makespan.
Dynamic scheduling using real-time data in manufacturing systems enables quick response to unforeseen system events to reduce costs and makespan while increasing customer satisfaction. Since many production systems are multi-product, each product’s customers aim to receive the product in the shortest possible time, thus competing with each other. Extant research neglects to consider not only competition between customers, but also bargaining strategies. In this paper, a hybrid flow shop system with multi-product is regarded. The production system studied is the Alborz Tire Company (Iran), which uses multi-type machines subject to stochastic failure. The objective is to determine the product processing prioritization in workstations, based on the Nash bargaining model, to minimize makespan. To this end, a simulation–optimization approach based on discrete-event simulation and Simulated annealing is employed. The results of the case study show that makespan is reduced significantly for all players. |
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| AbstractList | Dynamic scheduling using real-time data in manufacturing systems enables quick response to unforeseen system events to reduce costs and makespan while increasing customer satisfaction. Since many production systems are multi-product, each product's customers aim to receive the product in the shortest possible time, thus competing with each other. Extant research neglects to consider not only competition between customers, but also bargaining strategies. In this paper, a hybrid flow shop system with multi-product is regarded. The production system studied is the Alborz Tire Company (Iran), which uses multi-type machines subject to stochastic failure. The objective is to determine the product processing prioritization in workstations, based on the Nash bargaining model, to minimize makespan. To this end, a simulation–optimization approach based on discrete-event simulation and Simulated annealing is employed. The results of the case study show that makespan is reduced significantly for all players. •Proposing a game-based simulation–optimization approach in HFS scheduling.•Using bargaining approach to determine the optimal priority processing rule in HFS.•Using scheduling game in an HFS exposed to the stochastic failure of machinery.•The efficiency of the approach due to the significant reduction of makespan. Dynamic scheduling using real-time data in manufacturing systems enables quick response to unforeseen system events to reduce costs and makespan while increasing customer satisfaction. Since many production systems are multi-product, each product’s customers aim to receive the product in the shortest possible time, thus competing with each other. Extant research neglects to consider not only competition between customers, but also bargaining strategies. In this paper, a hybrid flow shop system with multi-product is regarded. The production system studied is the Alborz Tire Company (Iran), which uses multi-type machines subject to stochastic failure. The objective is to determine the product processing prioritization in workstations, based on the Nash bargaining model, to minimize makespan. To this end, a simulation–optimization approach based on discrete-event simulation and Simulated annealing is employed. The results of the case study show that makespan is reduced significantly for all players. |
| ArticleNumber | 115066 |
| Author | Khalili-Damghani, Kaveh Hafezalkotob, Ashkan Malekpour, Hiva |
| Author_xml | – sequence: 1 givenname: Hiva surname: Malekpour fullname: Malekpour, Hiva – sequence: 2 givenname: Ashkan orcidid: 0000-0002-6637-5716 surname: Hafezalkotob fullname: Hafezalkotob, Ashkan email: a_hafez@azad.ac.ir, ashkan.hafez@gmail.com – sequence: 3 givenname: Kaveh orcidid: 0000-0002-2338-1673 surname: Khalili-Damghani fullname: Khalili-Damghani, Kaveh |
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| SubjectTerms | Bargaining Customer satisfaction Discrete event systems Discrete-event simulation Game scheduling Hybrid systems Job shops Nash bargaining Optimization Simulated annealing Simulation Simulation-optimization Workstations |
| Title | Product processing prioritization in hybrid flow shop systems supported on Nash bargaining model and simulation-optimization |
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