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
Nemat Allah Taghi-Nezhad; Fatemeh Taleshian
Abstract
Quadratic Programming has been widely applied to solve real-world problems. This paper describes a solution method for solving a special class of fuzzy quadratic programming problems with fuzziness in relations. Then the method is generalized to a more general fuzzy quadratic programming problem, where ...
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Quadratic Programming has been widely applied to solve real-world problems. This paper describes a solution method for solving a special class of fuzzy quadratic programming problems with fuzziness in relations. Then the method is generalized to a more general fuzzy quadratic programming problem, where the cost coefficients, the matrix of the quadratic form, constraints coefficients, and the right-hand sides are all fuzzy numbers. Finally, some examples are taken to the utility of our proposed method.
