data envelopment analysis (dea) is a technique used to evaluate the relative efficiency of comparable decision making units (dmus) with multiple input-output. it computes a scalar measure of efficiency and discriminates between efficient and inefficient dmus. it can also provide reference units for inefficient dmus without consideration of the decision makers’ (dms) preferences. in this paper, ...

Computing the exact ideal and nadir criterion values is a very ‎important subject in ‎multi-‎objective linear programming (MOLP) ‎problems‎‎. In fact‎, ‎these values define the ideal and nadir points as lower and ‎upper bounds on the nondominated points‎. ‎Whereas determining the ‎ideal point is an easy work‎, ‎because it is equivalent to optimize a ‎convex function (linear function) over a con...

Data envelopment analysis (DEA) is a technique used to evaluate the relative efficiency of comparable decision making units (DMUs) with multiple input-output. It computes a scalar measure of efficiency and discriminates between efficient and inefficient DMUs. It can also provide reference units for inefficient DMUs without consideration of the decision makers’ (DMs) preferences. In this paper, ...

A characteristic of data envelopment analysis (DEA) is to allow individual decision making units (DMUs) to select the most advantageous weights in calculating their efficiency scores. This flexibility, 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 scale, this paper proposes using a multiple objective...

MCDA in general and multiple objective linear programming (MOLP) in particular can be used for planning future performances. The model structures of DEA and MOLP have much in common and research on integrating DEA and MOLP has attracted increasing attentions to support both past performance assessment and future target setting in integrated manners (Cooper, 2004). For instance, Golany (1988) de...

Data envelopment analysis (DEA) and multiple objective linear programming (MOLP) are tools that can be used in management control and planning. Whilst these two types of model are similar in structure, DEA is directed to assessing past performances as part of management control function and MOLP to planning future performance targets. Several equivalence models between the output-oriented DEA a...

Abstract In this paper, by using Data Envelopment Analysis (DEA) technique a method is proposed to find efficient solutions of 0-1 Multiple Objective Linear Programming (MOLP) problem. In this method from a feasible solution of 0-1 MOLP problem, a Decision Making Unit (DMU) without input vector is constructed in which output vector for DMU is the values of objective functions. The method consis...

In this paper we investigate inputs/outputs estimate in the presence of undesirable factors. We discuss such questions: suppose some outputs (inputs) are undesirable and among a group of decision making units (DMUs) a DMU changes (increases and decreases simultaneously) some of its input (output) levels, how much outputs (inputs) could the unit change such that its efficiency index remains unch...

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 ...