A communication procedure for communicating scheduling expert systems based on fuzzy set theory is proposed. Fuzzy sets are used to express and to exchange constraints and their possible relaxations with other scheduling systems that can interpret these constraints. The procedure is intended to optimize the global evaluation among the communicating systems. An example from steel industry is tak...

Vagueness is often considered as an inherent property of spatiotemporal phenomena. In order to reduce this vagueness, integrity constraints should be defined to improve logical consistency of spatiotemporal databases. However, existing constraints are not adapted to control logical consistency of vague spatiotemporal objects because they are initially defined for crisp (or non–fuzzy) objects. W...

quality of products and services is considered as a key factor for customer satisfaction. quality function deployment (qfd) is known as a critical tool for translating voice of customers to prioritize technical requirements of a production. the level of this satisfaction depends on the number of fulfilled requirements. it should be noted that this level varies according to the possible constrai...

This paper outlines two contributions to stability analysis of fuzzy systems: knowledge of the membership function shape (actually, constraints on the membership function values) and polynomial approaches. Both ideas reduce the conservativeness in the stability analysis of a nonlinear system when expressed as a fuzzy model by using membership shape information and by allowing a more general cla...

‘‘Is there a need for fuzzy logic?” is an issue which is associated with a long history of spirited discussions and debate. There are many misconceptions about fuzzy logic. Fuzzy logic is not fuzzy. Basically, fuzzy logic is a precise logic of imprecision and approximate reasoning. More specifically, fuzzy logic may be viewed as an attempt at formalization/mechanization of two remarkable human ...

There are several methods for solving fuzzy linear programming (FLP)problems. When the constraints and/or the objective function are fuzzy, the methodsproposed by Zimmermann, Verdegay, Chanas and Werners are used more often thanthe others. In the Zimmerman method (ZM) the main objective function cx is addedto the constraints as a fuzzy goal and the corresponding linear programming (LP)problem w...

In this paper, we concentrate on discussing the inventory problem under bifuzzy environment and develop a class of multi-objective inventory model with bifuzzy coefficients. We give the bifuzzy transform operarion and prove the method of solving satisfied solution of multi-objective inventory model. These are applied to a practical inventory problem in which all inventory costs, purchasing and ...

Given a fuzzy variable, what is the degree of difficulty of predicting the specified value that the fuzzy variable will take? Entropy provides a measure to characterize the fuzziness. Given some constraints, there are usually multiple compatible membership functions. Which membership function shall we take? The maximum entropy principle attempts to select the membership function that maximizes ...

In practice, there are many problems which decision parameters are fuzzy numbers, and some kind of this problems are formulated as either possibilitic programming or multi-objective programming methods. In this paper, we consider a multi-objective programming problem with fuzzy data in constraints and introduce a new approach for solving these problems base on a combination of the multi-objecti...