Designing a manufacturing cell system by assigning workforce

Artikel

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Journal of Industrial Engineering and Management (JIEM) ; ISSN: 2013-0953 ; Volume: 12 ; Year: 2019 ; Issue: 1 ; Pages: 13-26 ; Barcelona: OmniaScience

Classification and Topics

• Classification: Management
• Subject: Cell production ; group technology ; particle Swarm algorithm ; simulated annealing algorithm

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Ayough, Ashkan ; Khorshidvand, Behrouz
• Event: Veröffentlichung
• (who): OmniaScience
• (where): Barcelona
• (when): 2019

Further information

• DOI: doi:10.3926/jiem.2547
• Handle: http://hdl.handle.net/10419/261679
• Last update: 10.03.2025, 11:44 AM CET