a characteristic of data envelopment analysis (dea) is to allow individual decision making units (dmus) to select the factor weights which are the most advantageous for them in calculating their efficiency scores. this flexibility in selecting the weights, on the other hand, deters the comparison among dmus on a common base. for dealing with this difficulty and assessing all the dmus on the sam...

a characteristic of data envelopment analysis (dea) is to allow individual decision making units (dmus) to select the factor weights which are the most advantageous for them in calculating their efficiency scores. this flexibility in selecting the weights, on the other hand, deters the comparison among dmus on a common base. for dealing with this difficulty and assessing all the dmus on the sam...

a characteristic of data envelopment analysis (dea) is to allow individual decision making units (dmus) to select the factor weights that are the most advantages for them in calculating their efficiency scores. this flexibility in selecting the weights, on the other hand, deters the comparison among dmus on a common base. for dealing with this difficulty and assessing all the dmus on the same s...

We develop in this article a geometric approach to duality in Multiple Objective Linear Programming. This approach is based on a very old idea, the duality of polytopes, which can be traced back to the old Greeks. We show that there is an inclusion reversing one-to-one map between the minimal faces of the image of the primal objective and the maximal faces of the image of the dual objective map.

The application of fuzzy approach models to forecast has been drawing a lot of attention. This study proposes a fuzzy approach to forecasting using a financial data set. The methodology used is multiple objective linear programming (MOLP). Selecting an individual forecast based upon a single objective may not make the best use of available information for a variety of reasons. Combined forecast...

We discuss two approaches to duality for multiple objective linear problems. The first approach is based on a duality relation between a set and its complement in the outcome space. It allows us to obtain a number of known duality constructions. The second approach utilizes polarity between a polyhedral set and the epigraph of its support function. It leads to a parametric dual problem which is...

It is generally accepted that Data Envelopment Analysis (DEA) is a method for indicating efficiency. The DEA method has many applications in the field of calculating the relative efficiency of Decision Making Units (DMU) in explicit input-output environments. Regarding imprecise data, several definitions of efficiency can be found. The aim of our work is showing an equivalence relation between ...

In this paper we study the bilevel linear programming problem with multiple objective functions at the upper level, with particular focus on the bi-objective case. We examine some properties of this problem and propose a methodological approach based on the reformulation of the problem as a multiobjective mixed 0-1 linear programming problem. The basic idea consists in applying a reference poin...

An interactive fuzzy multiple objective optimization method was proposed for solving fuzzy multiple objective linear programming problems where fuzzy parameters in both objective functions and constraints and fuzzy goals of objectives can be in any form of membership function. Based on the method, in this paper, a fuzzy multiple objective decision support system prototype is developed. A detail...