a fully fuzzy linear programming (fflp) formulation for the reservoir operation of amultipurpose reservoir in presented in the ongoing paper. in the real world, water resourcessystems usually have complexities among social, economic, natural resources andenvironmental aspects, which lead to multi-objective problems of significant uncertainties insystem parameters, objectives and in their intera...

there are two interesting methods, in the literature, for solving fuzzy linear programming problems in which the elements of coefficient matrix of the constraints are represented by real numbers and rest of the parameters are represented by symmetric trapezoidal fuzzy numbers. the first method, named as fuzzy primal simplex method, assumes an initial primal basic feasible solution is at hand. t...

The classification of fuzzy data is considered as the most challenging areas of data analysis and the complexity of the procedures has been obstacle to the development of new methods for fuzzy data analysis. However, there are significant advances in modeling systems in which fuzzy data are available in the field of mathematical programming. In order to exploit the results of the researches on ...

This paper proposes a compromise model, based on a new method, to solve the multiobjectivelarge scale linear programming (MOLSLP) problems with block angular structureinvolving fuzzy parameters. The problem involves fuzzy parameters in the objectivefunctions and constraints. In this compromise programming method, two concepts areconsidered simultaneously. First of them is that the optimal alter...

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 propo...

in this study, an outsourcer evaluation and management system is developed for a manufacturing company by use of fuzzy goal programming (fgp). a first phase of the methodology evaluation criteria for outsources and the objectives of the company are determined. considering the fuzziness in the decision data, linguistic variables that can be expressed in generalized fuzzy number are used. the pro...

in applications there occur different forms of uncertainty. the twomost important types are randomness (stochastic variability) and imprecision(fuzziness). in modelling, the dominating concept to describe uncertainty isusing stochastic models which are based on probability. however, fuzzinessis not stochastic in nature and therefore it is not considered in probabilisticmodels.since many years t...

The present paper aims to propose an alternative solution approach in obtaining the fuzzy optimal a linear programming problem with variables given as numbers minimum uncertainty. In this paper, problems is transformed into equivalent interval numbers. solutions these are then obtained help of technique. A set six random numerical examples has been solved using proposed approach.

This paper is concerned with the fuzzy support vector classification, in which both of the type of the output training point and the value of the final fuzzy classification function are triangle fuzzy number. First, the fuzzy classification problem is formulated as a fuzzy chance constrained programming. Then, we transform this programming into its equivalence quadratic programming. Final, a fu...

On the basis of the possibility measure, necessity measure, credibility measure and probability measure, chance-constrained programming models are designed to treat optimization problems with stochastic and fuzzy parameters. Then, mathematical properties of different models, for instance, crisp equivalents of uncertain functions and constraints, are discussed on condition that parameters are un...