Artikel
Designing a manufacturing cell system by assigning workforce
Purpose: In this paper, we have proposed a new model for designing a Cellular Manufacturing System (CMS) for minimizing the costs regarding a limited number of cells to be formed by assigning workforce. Design/methodology/approach: Pursuing mathematical approach and because the problem is NP-Hard, two meta-heuristic methods of Simulated Annealing (SA) and Particle Swarm Optimization (PSO) algorithms have been used. A small randomly generated test problem with real-world dimensions has been solved using simulated annealing and particle swarm algorithms. Findings: The quality of the two algorithms has been compared. The results showed that PSO algorithm provides more satisfactory solutions than SA algorithm in designing a CMS under uncertainty demands regarding the workforce allocation. Originality/value: In the most of the previous research, cell production has been considered under certainty production or demand conditions, while in practice production and demand are in a dynamic situations and in the real settings, cell production problems require variables and active constraints for each different time periods to achieve better design, so modeling such a problem in dynamic structure leads to more complexity while getting more applicability. The contribution of this paper is providing a new model by considering dynamic production times and uncertainty demands in designing cells.
- Sprache
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Englisch
- Erschienen in
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Journal: Journal of Industrial Engineering and Management (JIEM) ; ISSN: 2013-0953 ; Volume: 12 ; Year: 2019 ; Issue: 1 ; Pages: 13-26 ; Barcelona: OmniaScience
- Klassifikation
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Management
- Thema
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Cell production
group technology
particle Swarm algorithm
simulated annealing algorithm
- Ereignis
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Geistige Schöpfung
- (wer)
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Ayough, Ashkan
Khorshidvand, Behrouz
- Ereignis
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Veröffentlichung
- (wer)
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OmniaScience
- (wo)
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Barcelona
- (wann)
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2019
- DOI
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doi:10.3926/jiem.2547
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:44 MEZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Ayough, Ashkan
- Khorshidvand, Behrouz
- OmniaScience
Entstanden
- 2019