Abstract
The paper proposes a fuzzy programming based approach to design a cellular manufacturing system under dynamic and uncertain conditions. The dynamic condition indicates a multi-period planning horizon, in which the product mix and demand in each period can be different. As a result, the best cells designed for one period may not be efficient cells for subsequent periods and some of reconfigurations are required. Uncertain condition implicates to the imprecise nature of the part demand and also the availability of the manufacturing facilities in each period planning. An extended mixed-integer programming model of dynamic cellular manufacturing system, in which some of the coefficients in objective function and constraints are fuzzy quantities, is solved by a developed fuzzy programming based approach. The objective is to determine the optimal cell configuration in each period with maximum satisfaction degree of the fuzzy objective and constraint. To illustrate the behavior of the proposed model and verify the performance of the developed approach, a number of numerical examples are solved and the associated computational results are reported.
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References
Arikan F., Gungor Z. (2005). A parametric model for cell formation and exceptional elements’ problems with fuzzy parameters. Journal of Intelligent Manufacturing, 16, 103–114
Askin R.G., Selim H.M., Vakharia A.J. (1997). A methodology for designing flexible cellular manufacturing systems. IIE Transactions, 29, 599–610
Balakrishnan J., Cheng C.H. (2005). Dynamic cellular manufacturing under multi-period planning Horizons. Journal of Manufacturing Technology Management, 16(5): 516–530
Bellman R.E., Zadeh L.A. (1970). Decision-making in a fuzzy environment. Management Science, 17, 141–164
Chen M. (1998). A mathematical programming model for systems reconfiguration in a dynamic cell formation condition. Annals of Operations Research, 77, 109–128
Drolet J., Abdulnour G., Rheault M. (1996). The cellular manufacturing evolution. Computers and Industrial Engineering, 31(1): 139–142
Gasimov R.N., Yenilmez k. (2002). Solving fuzzy linear programming problems with linear membership functions. Turkish Journal of Mathematics, 26, 375–396
Harhalakis G., Nagi R., Proth J. (1990). An effective heuristic in manufacturing cell formation for group technology applications. International Journal of Production Research, 28, 185–198
Herrera F., Verdegay J.L., Zimmermann H.J. (1993). Boolean programming problems with fuzzy constraints. Fuzzy Sets and Systems, 55(3): 285–293
Jeon G., Leep H.R. (2006). Forming part families by using genetic algorithm and designing machine cells under demand changes. Computers & Operations Research, 33, 263–283
Kannan V., Ghosh S. (1995). Using dynamic cellular manufacturing to simplify scheduling in cell based production systems. Omega, 23(4): 443–452
Klir, G. J., & Yuan, B. (1995). Fuzzy sets and fuzzy logic-theory and applications (p. 574). Prentice-Hall Inc.
Lai Y.-J., Hwang C.-L. (1992). Fuzzy mathematical programming: Methods and applications. Heidelberg, Springer-Verlag
Marcoux Y., Drolet J., Abdulnour G. (1997). Studying the performance Of a dynamic cellular manufacturing system. Computers and Industrial Engineering, 33(1): 239–242
Rheault M., Drolet J., Abdulnour G. (1995). Physically reconfigurable virtual cells: A dynamic model for a highly dynamic environment. Computers and Industrial Engineering, 29(1–4): 221–225
Saidi-Mehrabad, M., & Safaei, N. (2006). A new model of dynamic cell formation by a neural approach. International Journal of Advanced Manufacturing Technology, DOI 10.1007/s00170-006-0518-2, Article in press.
Shanker R., Vrat P. (1999). Some design issues in cellular manufacturing using the fuzzy programming approach. International Journal of Production Research, 37(11): 2545–2563
Song S., Hitomi K. (1996). Integrating the production planning and cellular layout for flexible cellular manufacturing. International Journal of Production. Planning and Control, 7, 585–593
Tavakkoli-Moghaddam R., Aryanezhad M.B., Safaei N., Azaron A. (2005). Solving a dynamic cell formation problem using metaheuristics. Applied Mathematics and Computation, 170(2): 761–780
Tsai C.C., Chu C.H., Barta T.A. (1997). Modeling and analysis of a manufacturing cell formation problem with fuzzy mixed integer programming. IIE Transactions, 29, 533–547
Vakharia A.J., Kaku B.K. (1993). Redesigning a cellular manufacturing system to handle long-term demand changes: A methodology and investigation. Decision Sciences, 24(5): 909–929
Wicks E.M., Reasor R.J. (1999). Designing cellular manufacturing systems with dynamic part populations. IIE Transactions, 31, 11–20
Wilhelm W., Chou C., Chang D. (1998). Integrating design and planning considerations in cell formation. Annals of Operations Research, 77, 97–107
Zimmermann H.J. (1978). Fuzzy programming and linear programming with several Objective functions. Fuzzy Sets and Systems, 1, 45–55
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Safaei, N., Saidi-Mehrabad, M. & Babakhani, M. Designing cellular manufacturing systems under dynamic and uncertain conditions. J Intell Manuf 18, 383–399 (2007). https://doi.org/10.1007/s10845-007-0029-5
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DOI: https://doi.org/10.1007/s10845-007-0029-5