Designing cellular manufacturing systems under dynamic and uncertain conditions
- 177 Downloads
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.
KeywordsDynamic cellular manufacturing systems Uncertain environment Fuzzy Linear programming
Unable to display preview. Download preview PDF.
- Askin R.G., Selim H.M., Vakharia A.J. (1997). A methodology for designing flexible cellular manufacturing systems. IIE Transactions, 29, 599–610Google Scholar
- Gasimov R.N., Yenilmez k. (2002). Solving fuzzy linear programming problems with linear membership functions. Turkish Journal of Mathematics, 26, 375–396Google Scholar
- Klir, G. J., & Yuan, B. (1995). Fuzzy sets and fuzzy logic-theory and applications (p. 574). Prentice-Hall Inc.Google Scholar
- Lai Y.-J., Hwang C.-L. (1992). Fuzzy mathematical programming: Methods and applications. Heidelberg, Springer-VerlagGoogle Scholar
- 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.Google Scholar
- 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, 533–547Google Scholar
- Wicks E.M., Reasor R.J. (1999). Designing cellular manufacturing systems with dynamic part populations. IIE Transactions, 31, 11–20Google Scholar