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Cell forming and cell balancing of virtual cellular manufacturing systems with alternative processing routes using genetic algorithm | ||
Journal of Optimization in Industrial Engineering | ||
مقاله 6، دوره 9، شماره 20، آذر 2016، صفحه 41-51 اصل مقاله (2.23 M) | ||
نوع مقاله: Original Manuscript | ||
شناسه دیجیتال (DOI): 10.22094/joie.2016.249 | ||
نویسندگان | ||
Adib Hosseini1؛ Mohammad Mahdi Paydar2؛ Iraj Mahdavi* 1؛ Javid Jouzdani3 | ||
1Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran | ||
2Department of Industrial Engineering, Babol Noshirvani University of Technology | ||
3PhD, Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran | ||
چکیده | ||
Cellular manufacturing (CM) is one of the most important subfields in the design of manufacturing systems and as a recently emerged field of study and practice, virtual cellular manufacturing (VCM) inherits the importance from CM. One type of VCM problems is VCM with alternative processing routes from which the route for processing each part should be selected. In this research, a bi-objective mathematical programming model is designed in order to obtain optimal routing of parts, the layout of machines and the assignment of cells to locations and to minimize the production costs and to balance the cell loads. The proposed mathematical model is solved by multi-choice goal programming (MCGP). Since CM models are NP-Hard, a genetic algorithm (GA) is utilized to solve the model for large-sized problem instances and the results obtained from both methods are compared. Finally, a conclusion is made and some visions for future works are offered. Cellular manufacturing (CM) is one of the most important subfields in the design of manufacturing systems and as a recently emerged field of study and practice, virtual cellular manufacturing (VCM) inherits the importance from CM. One type of VCM problems is VCM with alternative processing routes from which the route for processing each part should be selected. In this research, a bi-objective mathematical programming model is designed in order to obtain optimal routing of parts, the layout of machines and the assignment of cells to locations and to minimize the production costs and to balance the cell loads. The proposed mathematical model is solved by multi-choice goal programming (MCGP). Since CM models are NP-Hard, a genetic algorithm (GA) is utilized to solve the model for large-sized problem instances and the results obtained from both methods are compared. Finally, a conclusion is made and some visions for future works are offered. | ||
تازه های تحقیق | ||
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کلیدواژهها | ||
Virtual Cellular Manufacturing؛ Mathematical Programming؛ Multi-Choice Goal Programming؛ Genetic Algorithm | ||
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