in this paper, we show that inverse data envelopment analysis (dea) models can be used to estimate output with fuzzy data for a decision making unit (dmu) when some or all inputs are increased and deficiency level of the unit remains unchanged.

In this paper fully fuzzy linear programming (FFLP) problem with both equality and inequality constraints is considered where all the parameters and decision variables are represented by non-negative trapezoidal fuzzy numbers. According to the current approach, the FFLP problem with equality constraints first is converted into a multi–objective linear programming (MOLP) problem with crisp const...

There are varieties of QFD combination forms available that can help management to choose the right model for his/her types of problem. The proposed MOCC-QFD-FMEA model is a right model to include variety of objectives as well as the risk factors into the model of the problem. Due to the fact that the model also takes into consideration the concept of Fuzzy set, it further allows management...

-A neural network approach for solving fuzzy linear programming problems is proposed in which fuzzy concepts are not used. This approach is totally based on the level-sum method introduced Pandian [11]. The nearest optimal solution of the fuzzy linear programming original problem can be obtained by the proposed approach. The large scale fuzzy linear programming problems can be solved efficientl...

in this paper a non linear integrated fuzzy multi-objective production planning model with the labor learning and machines deterioration effects is presented. the objective function consists of two quantitative objectives namely increase profits and reduces the cost of system failure and a qualitative objective namely increases the satisfaction rate of the customers. different weights for objec...

In the present paper, the multi-objective solid transportation problem with fuzzy coefficients for the objectives and constraints is modelled and then solved. Fuzzy goal programming is used to the linear multiobjective solid transportation problem, and an optimal compromise solution is obtained. Firstly, expected values of the fuzzy objective functions are considered to derive crisp values. In ...

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Classically, most programming languages use in a predefined way the notion of “string” as an standard data structure for a comfortable management of arbitrary sequences of characters. However, in this paper we assign a different role to this concept: here we are concerned with fuzzy logic programming, a somehow recent paradigm trying to introduce fuzzy logic into logic programming. In this sett...

The problem of solving a multi-objective programming problem, by assuming that the decision maker has fuzzy goals for each of the objectives, is addressed. In this case a fuzzy goal programming problem has to be solved. But when we have several objectives it can be a difficult task for the decision maker to determine coherent aspiration levels, so it is possible that the tolerance thresholds be...

This paper proposes a new method for solving a multi-objective linear programming model with fuzzy random variables. In this model, a multi-objective linear programming problem with real variables and fuzzy random coefficients is introduced. Then, a new algorithm is developed to solve the model based on the concepts of mean value of fuzzy random variables, chance-constrained programming and pie...