Fuzzy optimization
Faranak Mahmoudi; Seyed Hadi Nasseri
Abstract
Today, human decisions are more than ever based on information. But most of this information is not definitive, and in this situation, logical decision making is very difficult based on this uncertainty. Different methods are used to represent this uncertainty, including the fuzzy numbers. The fuzzy ...
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Today, human decisions are more than ever based on information. But most of this information is not definitive, and in this situation, logical decision making is very difficult based on this uncertainty. Different methods are used to represent this uncertainty, including the fuzzy numbers. The fuzzy linear programming problem is one of the interesting concepts to be addressed in fuzzy optimization. Fully Fuzzy Linear Programming Problems (FFLP) are issues in which all parameters of the coefficients of the variables in the target functions, the coefficients of the variables in the constraints, the right-hand side of the constraints, and the decision variables in them are fuzzy. In this paper, we show that Definition 2.6 which is used by Ezzati et al. [1], failed to compare any arbitrary triangular fuzzy numbers. We demonstrate that their presented method is not well in general, thus the proposed method finds the fuzzy optimal solution of fully fuzzy linear programming problems by Ezzati et al. [1]. Then a new approach is proposed for solving this FFLP problem. An example is also presented to demonstrate the new method.
Fuzzy optimization
Sapan Kumar Das; Tarni Mandal
Abstract
In this paper, we studied fuzzy linear fractional programming (FLFP) problems with trapezoidal fuzzy numbers where the objective functions are fuzzy numbers and the constraints are real numbers. In this study, in order to obtain the fuzzy optimal solution with unrestricted variables and parameters, a ...
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In this paper, we studied fuzzy linear fractional programming (FLFP) problems with trapezoidal fuzzy numbers where the objective functions are fuzzy numbers and the constraints are real numbers. In this study, in order to obtain the fuzzy optimal solution with unrestricted variables and parameters, a new efficient method for FLFP problem has been proposed. These proposed methods are based on crisp linear fractional programming and newly transformation technique is also used. A computational procedure has been presented to obtain an optimal solution. To show the efficiency of our proposed method a real life example has been illustrated.
Fuzzy optimization
Ranjan Kumar; Sripati Jha; Ramayan Singh
Abstract
In traditional shortest path problem it is always determined that the parameters (Time, Cost and Distance etc.) are fixed between different nodes. But in real life situations where uncertain parameters exist, parameters are considered as fuzzy numbers. In this paper, we explained the application ...
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In traditional shortest path problem it is always determined that the parameters (Time, Cost and Distance etc.) are fixed between different nodes. But in real life situations where uncertain parameters exist, parameters are considered as fuzzy numbers. In this paper, we explained the application scope of the given fuzzy ranking function. Using this method we can determine both the fuzzy shortest path and fuzzy shortest Distance from origin to Destination.
