In this paper, a linear optimization problem is investigated whose constraints are defined with fuzzy relational inequality. These constraints are formed as the intersection of two inequality fuzzy systems and Schweizer-Sklar family of t-norms. Schweizer-Sklar family of t-norms is a parametric family of continuous t-norms, which covers the whole spectrum of t-norms when the parameter is changed...

In this paper, we study the finitely many constraints of fuzzy relation inequalities problem and optimize the linear objective function on this region which is defined with fuzzy max-Lukasiewicz operator. In fact Lukasiewicz t-norm is one of the four basic t-norms. A new simplification technique is given to accelerate the resolution of the problem by removing the components having no effect on ...

An architecture and a 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 potential relaxation with the cooperating scheduling system that can interpret these constraints. The procedure is intended to optimize the global evaluation among the communicating systems. An example from steel ...

This paper presents a method to solve a linear or nonlinear Fuzzy Multiobjective Programming problem. We propose Genetic Search based approaches to the case in which fuzzy constraints are assumed.

In this paper we propose a propositional temporal language based on fuzzy temporal constraints which turns out to be expressive enough for domains –like many coming from medicine– where knowledge is of propositional nature and an explicit handling of time, imprecision and uncertainty are required. The language is provided with a natural possibilistic semantics to account for the uncertainty iss...

Ronald R. Yager Machine Intelligence Institute, Iona College New Rochelle, NY 10801 [email protected] (212)249-2047 ABSTRACT Fuzzy sets and other methods have been used to model a softening of constraints in CP problems. Here we suggest an approach to the softening of the CP problem at the meta level, the process used to aggregate the satisfactions to the individual constraints. We suggest the us...

In this paper, a parametric method is introduced to solve fuzzy transportation problem. Considering that parameters of transportation problem have uncertainties, this paper develops a generalized fuzzy transportation problem with fuzzy supply, demand and cost. For simplicity, these parameters are assumed to be fuzzy trapezoidal numbers. Based on possibility theory and consistent with decision-m...

In this paper, an active learning method which can effectively select pairwise constraints during clustering procedure was presented. A novel semi-supervised text clustering algorithm was proposed, which employed an effective pairwise constraints selection method. As the samples on the fuzzy boundary are far away from the cluster center in the clustering procedure, they can be easily divided in...

QoS (Quality of Service) routing is a key network function for the transmission and distribution of digitized audio/video across next-generation high-speed networks. It has two objectives: finding routes that satisfy the QoS constraints and making efficient use of network resources. The complexity involved in the networks may require the consideration of multiple constraints to make the routing...

In this paper we focus on a kind of quadratic programming with fuzzy numbers and variables. First by using a fuzzy ranking and arithmetic operations, we transform these problems to crisp model with non-linear objective and linear constraints, then by solving this problem we obtain a fuzzy optimal solution. Finally, we give an illustrative example. 2000 Mathematics Subject Classification: 90C70,...