نتایج جستجو برای: fuzzy random programming
تعداد نتایج: 682177 فیلتر نتایج به سال:
Since most real-world decision problems, because of incomplete information or the existence of linguistic information in the data are including uncertainties. Stochastic programming and fuzzy programming as two conventional approaches to such issues have been raised. Stochastic programming deals with optimization problems where some or all the parameters are described by stochastic variables. I...
In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stochastic linear programming problems, but also multiobjective fuzzy random linear programming problems through a probability maximization model. In a probability maximization model, it is necessary for the decision maker to specify permissible values of objective functions in advance, which have a great infl...
In this paper, two kinds of fuzzy approaches are proposed for not only multiobjective stochastic linear programming problems, but also multiobjective fuzzy random linear programming problems through a probability maximization model. In a probability maximization model, it is necessary for the decision maker to specify permissible values of objective functions in advance, which have a great infl...
This paper considers multiobjective linear programming problems where each coefficient of the objective functions is expressed by a random fuzzy variable. A new decision making model is proposed by incorporating the concept of fractile criteria optimization into a possibilistic programming model. An interactive fuzzy satisficing method is presented for deriving a satisficing solution for a deci...
The Bayesian reliability estimation under fuzzy environments is proposed in this paper. In order to apply the Bayesian approach, the fuzzy parameters are assumed to be fuzzy random variables with fuzzy prior distributions. The (conventional) Bayesian estimation method will be used to create the fuzzy Bayes point estimator of reliability by invoking the well-known theorem called ‘Resolution Iden...
generally, an engineering design problem has multiple objective functions. some of these problems can be formulated as multiobjective geometric programming models. on the other hand,often in the real world, coefficients of the objective functions are not known precisely. coefficients may be interpreted as fuzzy numbers, which lead to a multiobjective geometric programming with fuzzy parameters....
fuzzy linear programming models and methods has been one ofthe most and well studied topics inside the broad area of soft computing. itsapplications as well as practical realizations can be found in all the real worldareas. in this paper a basic introduction to the main models and methods infuzzy mathematical programming, with special emphasis on those developedby the authors, is presented. as ...
Techniques for using the Monte Carlo method to evaluate fuzzy Riemann integrals and improper fuzzy Riemann integrals are proposed in this paper. Owing to the α-level set of the (improper) fuzzy Riemann integral being the closed interval whose end points are the classical (improper) Riemann integrals, it is possible to invoke the Monte Carlo method to approximate the end points of the α-level cl...
The fuzzy approach has undergone a profound structural transformation in the past few decades. Numerous studies have been undertaken to explain fuzzy approach for linear and nonlinear programs. While, the findings in earlier studies have been conflicting, recent studies of competitive situations indicate that fractional programming problem has a positive impact on comparative scenario. We pro...
Nowadays Geometric Programming (GP) problem is a very popular problem in many fields. Each type of Fuzzy Geometric Programming (FGP) problem has its own solution. Sometimes we need to use the ranking function to change some part of GP to the linear one. In this paper, first, we propose a method to solve multi-objective geometric programming problem with trapezoidal fuzzy variables; then we use ...
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