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Fuzzy solution in fuzzy linear programming problems

IEEE Transactions on Systems, Man, and Cybernetics, 1984
Conventional mathematical programming problems are to maximize an objective function subject to constraints. In the real decision problems, however, a satisfaction criterion might be more useful than a criterion of maximizing an objective function in making the decision under fuzzy constraints.
Hideo Tanaka, Kiyoji Asai
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Fuzzy linear programs with trapezoidal fuzzy numbers

Annals of Operations Research, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
K. Ganesan 0002, P. Veeramani
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Fuzzy relation linear programming

2009 IEEE International Conference on Granular Computing, 2009
In this paper, firstly, we present fuzzy relation linear programming with fuzzy objective coefficients, it is expanded to conventional fuzzy relation linear programming with crisp objective coefficients. Secondly, a solution procedure is given based on a norm of trapezoid fuzzy number. And finally, A numerical example is given for illustration purpose.
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Media Selection and Fuzzy Linear Programming

Journal of the Operational Research Society, 1978
Mathematical Programming models have been suggested as a tool for optimal media selection. In order to accommodate several objective functions goal programming models have been put forward. It seems, however, that these models are not yet operational and efficient enough to be used in practice.
Wiedey, G., Zimmermann, H.-J.
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A solution of linear programming with fuzzy variables

2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery, 2010
We introduce an approach to defuzzify a general fuzzy quantity, a general fuzzy number is approximated to its nearest symmetric trapezoidal fuzzy number. With the help of the above method, a fuzzy linear programming is converted to a linear programming with symmetric trapezoidal fuzzy variables.
Zhongxing Wang 0001   +2 more
openaire   +1 more source

Using fuzzy numbers in linear programming

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 1997
Managers, decision makers, and experts dealing with optimization problems often have a lack of information on the exact values of some parameters used in their problems. To deal with this kind of imprecise data, fuzzy sets provide a powerful tool to model and solve these problems.
José Manuel Cadenas, José L. Verdegay
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Fuzzy Linear Programming

2013
In 1976, Zimmermann first introduced fuzzy set theory into linear programming problems. He considered linear programming problems with a fuzzy goal and fuzzy constraints. Following the fuzzy decision proposed by Bellman and Zadeh (1970) together with linear membership functions, he proved that there exists an equivalent linear programming problem.
Masatoshi Sakawa   +2 more
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Bi-Level linear programming of intuitionistic fuzzy

Soft Computing, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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On fuzzy linear programming

European Journal of Operational Research, 1985
Fuzzy multi-objective and fuzzy goal programming are discussed in connection with several membership functions which are used to transform the original problem into three equivalent linear programming problems. Existence and uniqueness theorems are given.
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Fuzzy Linear Programming

2002
Most frequent mathematical programming problems are linear programming problems. In this chapter we are concerned with fuzzy linear programming problem related to linear programming problems in the following form.
Jaroslav Ramík, Milan Vlach
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