This paper proposes a compromise model, based on a new method, to solve the multi-objective large-scale linear programming (MOLSLP) problems with block angular structure involving fuzzy parameters. The problem involves fuzzy parameters in the objective functions and constraints. In this compromise programming method, two concepts are considered simultaneously. First of them is that the optimal ...

A multi-objective linear programming problem is made from fuzzy problem. It due the fact that it used method during solution. The Multi objective can be converted into single function by various methods as Chandra Sen’s method, weighted sum ranking statistical averaging method. In this paper, and both are here for making function. Two problems solved to verify result. One numerical example othe...

We present a logical framework to represent and reason about fuzzy optimization problems based on fuzzy answer set optimization programming. This is accomplished by allowing fuzzy optimization aggregates, e.g., minimum and maximum in the language of fuzzy answer set optimization programming to allow minimization or maximization of some desired criteria under fuzzy environments. We show the appl...

The linear programming technique for multidimensional analysis of preference (LINMAP) is one of the well-known methods for multiple attribute group decision making (MAGDM). In this paper, we extend the LINMAP method to solve MAGDM problems in interval-valued intuitionistic fuzzy environment in which all the preference information provided by the decisionmakers is presented as interval-valued in...

Abstract In this paper, the notions of subgradmnt, subdifferentla[, and differential with respect to convex fuzzy mappings are investigated, whmh provides the basis for the fuzzy extremum problem theory We consider the problems of minimizing or maximizing a convex fuzzy mapping over a convex set and develop the necessary and/or sufficient optlmahty conditions. Furthermore, the concept of saddle...

Three types of fuzzy random programming for capacitated location-allocation problem with fuzzy random demands are proposed according to different criteria, including the expected value model, chanceconstrained programming and dependent-chance programming. Finally, integrating the network simplex algorithm, fuzzy random simulation and genetic algorithm, a hybrid intelligent algorithm is produced...

Several authors have used ranking function for solving fuzzy linear programming problems. In this paper some fuzzy linear programming problems are chosen which can’t be solved by using any of the existing methods and a new method is proposed to solve such type of fuzzy linear programming problems. The main advantage of the proposed method over existing methods is that the fuzzy linear programmi...

In this paper, the authors present a methodology to solve the weighted barycenter problem when the data is inherently fuzzy. This method, from data clustered by expert visual inspection of maps, calculates bi-dimensional fuzzy numbers from the spatial clusters, which in turn are used to obtain the weighted fuzzy barycenter of a particular area. The authors apply the methodology, to a particular...