Linear programming (LP) is an optimisation technique most widely used for optimal allocation of limited resources amongst competing activities. Precise data are fundamentally indispensable in standard LP problems. However, the observed values of the data in real-world problems are often imprecise or vague. Fuzzy set theory has been extensively used to represent A fuzzy LP model with fuzzy param...

The task of a standard fuzzy logic controller is to find a crisp control action from the fuzzy rulebase and from a set of crisp inputs. In this paper we propose an extension of this type of reasoning using Mobile Agents which works with crisp data, intervals and/or linguistic terms as inputs and with various matching methods. For any matching one obtain a crisp value as output using Slave Agent...

This paper presents a general framework for the study of rough fuzzy sets in which fuzzy sets are approximated in a crisp approximation space. By the constructive approach, a pair of lower and upper generalized rough fuzzy approximation operators is first defined. The rough fuzzy approximation operators are represented by a class of generalized crisp approximation operators. Properties of rough...

This paper shows that the k-means quantization of a signal can be interpreted both as a crisp indicator function and as a fuzzy membership assignment describing fuzzy clusters and fuzzy boundaries. Combined crisp and fuzzy indicator functions are defined here as natural generalizations of the ordinary crisp and fuzzy indicator functions, respectively. An application to iris segmentation is pres...

We consider fuzzy stochastic programming problems with a crisp objective function and linear constraints whose coefficients are fuzzy random variables, in particular of type L-R. To solve this type of problems, we formulate deterministic counterparts of chance-constrained programming with fuzzy stochastic coefficients, by combining constraints on probability of satisfying constraints, as well a...

Many variants of fuzzy c-means (FCM) clustering method are applied to crisp numbers but only a few of them are extended to non-crisp numbers, mainly due to the fact that the latter needs complicated equations and exhausting calculations. Vector form of fuzzy c-means (VFCM), proposed in this paper, simplifies the FCM clustering method applying to non-crisp (symbolic interval and fuzzy) numbers. ...

In this paper we focus on linear fuzzy programming problems. The linear fuzzy programming problems will contain fuzzy constraints with a crisp objective function, crisp constraints with a fuzzy objective function, or fuzzy constraints with a fuzzy objective function. We propose here optimizing fuzzy constraints and objectives that consist of a triplet and are much like triangular fuzzy numbers,...

in previous studies we first concentrated on utilizing crisp simulationto produce discrete event fuzzy systems simulations. then we extendedthis research to the simulation of continuous fuzzy systems models. in this paperwe continue our study of continuous fuzzy systems using crisp continuoussimulation. consider a crisp continuous system whose evolution depends ondifferential equations. such a ...

In this paper, we introduce generalized directable fuzzy automaton and discuss their structural characterizations. We have shown that a generalized directable fuzzy automaton is an extension of a uniformly monogenically strongly directable fuzzy automaton by a uniformly monogenically trap-directable fuzzy automaton and obtain other equivalent conditions for a generalized directable fuzzy automa...