data envelopment analysis (dea) is a method to evaluate the relative efficiency of decision making units (dmus). in this method, the issue has always been to determine a set of weights for each dmu which often caused many problems. since the dea models also have the multi-objective linear programming (molp) problems nature, a rational relationship can be established between molp and dea problem...

this paper proposes a new approach for determining efficient dmus in dea models using inverse optimi-zation and without solving any lps. it is shown that how a two-phase algorithm can be applied to detect effi-cient dmus. it is important to compare computational performance of solving the simultaneous linear equa-tions with that of the lp, when computational issues and complexity analysis are a...

Abstract This study uses data envelopment analysis (DEA) approach to benchmark the performance of thirteen thrifts and mortgage finance companies against one another for the period 2008 to 2011. We cover the period of start of the economic crisis and the consequent passing to new law to regulate the financial services industry. We find that, at the height of the economic crisis in 2008, only fi...

In data envelopment analysis (DEA), mul-tiplier and envelopment CCR models eval-uate the decision-making units (DMUs) under optimal conditions. Therefore, the best prices are allocated to the inputs and outputs. Thus, if a given DMU was not efficient under optimal conditions, it would not be considered efficient by any other models. In the current study, using common weights in DEA, a number of...

This paper addresses comprehensive ranking systems determining an ordering of entities by aggregating quantitative data for multiple attributes. We propose a DEA-CP (Data Envelopment Analysis Compromise Programming) model for the comprehensive ranking, including preference voting (ranked voting) to rank candidates in terms of aggregate vote by rank for each candidate. Although the DEA-CP model ...

Conventional data envelopment analysis (DEA) models assume real-valued inputs and outputs. In many occasions, some inputs and/ or outputs can only take integer values. In some cases, rounding the DEA solution to the nearest whole number can lead to misleading efficiency assessments and performance targets. This paper develops the axiomatic foundation for DEA in the case of integer-valued data, ...

Data envelopment analysis (DEA) models have been used in formulating the Malmquist index to measure productivity change over time periods. In this article, we question the validity of this index in the presence of input/output slacks that appear in DEA models used. We demonstrate with an application to banking that Malmquist index loses its meaning whenever slacks are present. As a corrective m...

Some specific geometric data envelopment analysis (DEA) models are well known to the researchers in DEA through so-called multiplicative or log-linear efficiency models. Valuable properties of these models were noted by several authors but the models still remain somewhat obscure and rarely used in practice. The purpose of this paper is to show from a mathematical perspective where the geometri...

This paper presents a technique for comparing the results of different assembly line balancing strategies by using Data Envelopment Analysis (DEA). Initially, several heuristics— which can be thought of as assembly line balancing strategies—were used to solve seven line-balancing problems. The resulting line balance solutions provided two pieces of information that were of particular interest: ...

in this paper, a discrete event simulation model of iranian railway system is used for analyzing performance of the system in freight sector. the model analysis shows more sensitivity of the system on loading and unloading facilities than on number of wagons and locomotives. system optimization through simulation optimization technique, shows that more than 4% of all wagons available in the net...