majority of models in location literature are based on assumptions such as point demand, absence of competitors, as well as monopoly in location, products, and services. however in real-world applications, these assumptions are not well-matched with reality. in this study, a new mixed integer nonlinear programming model based on weighted goal programming approach is proposed to maximize the cap...

A non-linear multi-objective transportation problem (NMOTP) refers to a special class of non-linear multi-objective problems. In this paper we review goal programming (GP) and fuzzy programming (FP) as two approaches for solving (NMOTP). Meanwhile, by extending Mohamed’s idea about fuzzy goal programming (FGP), we propose a fuzzy goal programming approach to solve the non-linear multi-objective...

Traditional Data Envelopment Analysis (DEA) models evaluate the efficiency of decision making units (DMUs) with common crisp input and output data. However, the data in real applications are often imprecise or ambiguous. This paper transforms fuzzy fractional DEA model constructed using fuzzy arithmetic, into the conventional crisp model. This transformation is performed considering the goal pr...

the conceptualization of total economic value (tev) associated with protected natural areasnecessarily requires an analytical reordering that ensures a simultaneous incorporation of natural, social andeconomic components. based on this purpose, the present paper uses a multi-criteria decision modeling forthe economic valuation of environmental goods and services (egs) in the viñales national pa...

In this paper, we present modified fuzzy goal programming (FGP) approach and generalized MATLAB program for solving multi-level linear fractional programming problems (ML-LFPPs) based on with some major modifications in earlier FGP algorithms. In proposed modified FGP approach, solution preferences by the decision makers at each level are not considered and fuzzy goal for the decision vectors i...

A theorem was recently introduced to establish a relationship betweengoal programming and fuzzy programming for vectormaximum problems.In this short note it is shown that the relationship does not exist underall circumstances. The necessary correction is proposed.

The revised simplex method is often the method of choice when solving large scale sparse linear programming problems, particularly when a family of closely-related problems is to be solved. Each iteration of the revised simplex method requires the solution of two linear systems and a matrix vector product. For a significant number of practical problems the result of one or more of these operati...

this paper presents a fuzzy goal programming (fgp) methodology for solving bi-level quadratic programming (blqp) problems. in the fgp model formulation, firstly the objectives are transformed into fuzzy goals (membership functions) by means of assigning an aspiration level to each of them, and suitable membership function is defined for each objectives, and also the membership functions for vec...

multi objective quadratic fractional programming (moqfp) problem involves optimization of several objective functions in the form of a ratio of numerator and denominator functions which involve both contains linear and quadratic forms with the assumption that the set of feasible solutions is a convex polyhedral with a nite number of extreme points and the denominator part of each of the object...