Narasimhan incorporated fuzzy set theory within goal formulation in 1980. Since then, much research has been performed in this field, and various models for solving fuzzy goal programming have been proposed. One of the well-known models was proposed by Tiwari et al. in 1987 [19], where an additive model was proposed. This paper is an extension to the Tiwari et al. model that deals with the sum ...

This paper presents a goal programming model for problems where resources are defined by the opinion of multiple experts. Through the use of Type-2 fuzzy sets, we propose a model that includes human being like information in order to define the parameters of a goal programming problem, and then solve it using a constructive approach that uses LP models due to its efficiency. An application exam...

This paper presents fuzzy goal programming approach for solving multilevel programming problems with fuzzy parameters. The proposed approach is based on ? -cut and fuzzy goal programming. In the proposed approach, the tolerance membership functions for the fuzzily described objective functions are defined by determining individual best solution of the objective function of every decision maker....

In the present paper, the multi-objective solid transportation problem with fuzzy coefficients for the objectives and constraints is modelled and then solved. Fuzzy goal programming is used to the linear multiobjective solid transportation problem, and an optimal compromise solution is obtained. Firstly, expected values of the fuzzy objective functions are considered to derive crisp values. In ...

This paper considers two general 0-1 random fuzzy programming problems based on the degree of necessity which include some previous 0-1 stochastic and fuzzy programming problems. The proposal problems are not well defined due to including randomness and fuzziness. Therefore, by introducing chance constraint and fuzzy goal for the objective function, and considering the maximization of the aspir...

In the real situations, decision makers are often faced to a plurality of objectives and constraints in a world of imprecise data about the preferences of agents, the local constraints and the global environment. In a fuzzy environment, fuzzy linear programming (FLP) and fuzzy goal programming (FGP) problems incorporate fuzzy objective functions and constraints, fuzzy parameters and variable se...

This paper proposes a fuzzy goal programming based on Taylor series for solving decentralized bilevel multiobjective fractional programming (DBLMOFP) problem. In the proposed approach, all of the membership functions are associated with the fuzzy goals of each objective at the both levels and also the fractional membership functions are converted to linear functions using the Taylor series appr...

In this paper, a modified TOPSIS (techniques for order preference by similarity to ideal solution) approach for solving bi-level multi-objective programming (BL-MOP) problems with fuzzy parameters is presented. These fuzzy parameters are assumed to be characterized by fuzzy numerical data, reflecting the experts' imprecise or fuzzy understanding of the nature of the parameters in the problem fo...