Abstract
In this paper, limitations of the classical model of optimization are indicated and a more general model is given in terms of fuzzy subsets theory. The concept of a fuzzy value set of a function is defined and other important concepts involved in the model are established, based on the fuzzy value set. In this model an objective function and a constraint are symmetric. The former is only a special case of the latter. Moreover, the multiple objective problem and the single objective problem are also unified. Optimization problems often emerge in a fuzzy environment. A nonfuzzy environment is only its special case, so that this model is of great value in solving realistic problems of optimization in a large spectrum of fields. In this paper, a relationship between an optimal solution of fuzzy programming and important concepts of multiobjective programming, the efficient and weak-efficient solutions, is shown.
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© 1987 Springer Science+Business Media Dordrecht
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Yingjun, F. (1987). Fuzzy Programming — A New Model of Optimization. In: Kacprzyk, J., Orlovski, S.A. (eds) Optimization Models Using Fuzzy Sets and Possibility Theory. Theory and Decision Library, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-3869-4_15
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DOI: https://doi.org/10.1007/978-94-009-3869-4_15
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-8220-4
Online ISBN: 978-94-009-3869-4
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