Abstract
In conventional decision making problems, the estimation of the parameters of the model is often a problematic task. Normally they are either given by the decision maker (DM) who has imprecise information and/or expresses his/her considerations subjectively, or by statistical inference from past data and, consequently, their stability is doubtful. Therefore, it is reasonable to construct a model reflecting imprecise data or ambiguity in terms of fuzzy sets. This is the reason why a lot of fuzzy approaches to linear programming have been developed.
Our purpose in this paper is to present the solution of fuzzy linear programming problems in terms of a fuzzy number considered as a possibility distribution, i.e., the possibility distribution of the optimal value of the objective function. The method relies on α-cuts of the fuzzy solution to generate its possibility distribution. Finally, a bank balance sheet problem is solved for illustrating our approach.
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© 1998 Springer Science+Business Media New York
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Arenas, M.M., Bilbao, A., Rodríguez Uría, M.V., Jiménez, M. (1998). A Theory of Possibility Approach to The Solution of a Fuzzy Linear Programming. In: Girón, F.J. (eds) Applied Decision Analysis. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-0759-6_12
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DOI: https://doi.org/10.1007/978-94-017-0759-6_12
Publisher Name: Springer, Dordrecht
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