In the real-world optimization problems, coefficients of the objective function are not known precisely and can be interpreted as fuzzy numbers. In this paper we define the concepts of optimality for linear programming problems with fuzzy parameters (FLP). Then by using the concept of comparison of fuzzy numbers we transform FLP problem into a multiobjective linear programming (MOLP) problem. T...

In this paper we study fuzzy multiobjective optimization problems defined for $n$ variables.  Based on a new $p$-dimensional fuzzy stationary-point definition,  necessary  efficiency conditions are obtained.  And we prove that these conditions are also sufficient under new fuzzy generalized convexity notions. Furthermore, the results are obtained under general differentiability hypothesis.

Generalizing our earlier results on optimization with linguistic variables [3, 6, 7] we introduce a novel statement of fuzzy multiobjective mathematical programming problems and provide a method for findig a fair solution to these problems. Suppose we are given a multiobjective mathematical programming problem in which the functional relationship between the decision variables and the objective...

Generalizing our earlier results on optimization with linguistic variables [3, 6, 7] we introduce a novel statement of fuzzy multiobjective mathematical programming problems and provide a method for finding a fair solution to these problems. Suppose we are given a multiobjective mathematical programming problem in which the functional relationship between the decision variables and the objectiv...

1 Technical University of Cluj-Napoca Abstract -The paper proposes a new multiobjective optimization method, based on fuzzy techniques. The method performs a real multiobjective optimization, every parameter modification taking into account the unfulfillment degrees of all the requirements. It uses fuzzy sets to define fuzzy objectives and fuzzy systems to compute new parameter values. The stra...

Two major approaches to deal with randomness or impression involved in mathematical programming problems have been developed. The one is called stochastic programming, and the other is called fuzzy programming. In this paper, we focus on multiobjective integer programming problems involving random variable coefficients in constraints. Using the concept of simple recourse, such multiobjective st...

In this work we consider a multiobjective job shop problem with uncertain durations and crisp due dates. Ill-known durations are modelled as fuzzy numbers. We take a fuzzy goal programming approach to propose a generic multiobjective model based on lexicographical minimisation of expected values. To solve the resulting problem, we propose a genetic algorithm searching in the space of possibly a...

The multiobjective problem with fuzzy goals (which may also represent fuzzy right hand sides of the constraints) is formulated as a fuzzy goal programming problem. A new approach and a new solution method are proposed.

The classification of survival in severe burnt patients is an on-going problem. In this paper we propose a multiobjective optimisation model with constraints to obtain fuzzy classification models based on the criteria of accuracy and interpretability. We also describe a multiobjective evolutionary approach for fuzzy classification based on data with real and discrete attributes. This approach i...