A model for an integrated cellular manufacturing system with tools and operators assignment: Two tuned meta-heuristic algorithms
محورهای موضوعی : Operations Management
Omid Arghish
1
,
Reza Tavakkoli Moghaddam
2
1 - Assistant Professor, Department of Management, Fasa Branch, Islamic Azad university , Fasa, Iran. or Assistant Professor,Department Of Industrial Engineering, Gachsaran Branch, Islamic Azad University, Gachsaran, Iran
2 - Tehran University
کلید واژه: Cell formation, Cell layout, Taguchi method, Genetic algorithm, Harmony search.,
چکیده مقاله :
This paper presents a mathematical model for cell formation, cell layout, and resources assignment problems simultaneously. This model focuses on the influence of the man-machine relationship aspect on the cellular manufacturing system (CMS) design. The main purpose of the model is to demonstrate how to design the CMS with the new aspect such that the costs associated with processing, layout, worker, and machine idle time, machine and tool are minimized. The proposed model is applied to a numerical example using Lingo software. Due to the complexity of the presented model, a genetic algorithm (GA) is employed to find satisfactory solutions. To verify the solutions, a harmony search (HS) algorithm is used. Additionally, the Taguchi method is utilized to adjust the parameters in two proposed algorithms. Finally, to validate the model, some numerical examples are presented. Results emanating from the research show that the proposed HS algorithm is a favorable method for the presented model.
This paper presents a mathematical model for cell formation, cell layout, and resources assignment problems simultaneously. This model focuses on the influence of the man-machine relationship aspect on the cellular manufacturing system (CMS) design. The main purpose of the model is to demonstrate how to design the CMS with the new aspect such that the costs associated with processing, layout, worker, and machine idle time, machine and tool are minimized. The proposed model is applied to a numerical example using Lingo software. Due to the complexity of the presented model, a genetic algorithm (GA) is employed to find satisfactory solutions. To verify the solutions, a harmony search (HS) algorithm is used. Additionally, the Taguchi method is utilized to adjust the parameters in two proposed algorithms. Finally, to validate the model, some numerical examples are presented. Results emanating from the research show that the proposed HS algorithm is a favorable method for the presented model.
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