The purpose of this study is to utilize a new method for ranking extreme efficient decision making units (DMUs) based upon the omission of these efficient DMUs from reference set of inefficient and non-extreme efficient DMUs in data envelopment analysis (DEA) models with constant and variable returns to scale. In this method, an L2norm is used and it is believed that it doesn't have any existin...

Many types of facility location/allocation models have been developed to find optimal spatial patterns with respect to location criteria such as: cost, time, coverage, and access. In this paper we develop and test location modeling formulations that utilize aspects of the data envelopment analysis (DEA) efficiency measure to find optimal and efficient facility location/allocation patterns. Solv...

the aim of this research was to measure the relative efficiency of forest management plans in north of iran. in order to fulfill the research, data of 12 forest management plans were collected from the financial balance sheets of shafaroud forest company during a ten years period. first of all, basic data envelopment analysis (dea) models (bcc and ccr) were used to determine the efficiency. the...

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 ...

Group consensus ranking is an important topic in performance evaluation and selection research. Data envelopment analysis (DEA) has been used for obtaining an efficiency score (preference score) for each candidate. We propose an integrated DEA and simulation method for group consensus ranking. The ranking method proposed in this study has several unique features. In contrast to most voting meth...

One of the drawbacks of Data Envelopment Analysis (DEA) is the problem of lack of discrimination among efficient Decision Making Units (DMUs). A method for removing this difficulty is called changing reference set proposed by Jahanshahloo and et.al (2007). The method has some drawbacks. In this paper a modified method and new method to overcome this problems are suggested. The main advantage of...

data envelopment analysis (dea) was developed to help compare the relative performance of decision-making units. it is a non-parametric method for performing frontier analysis. it uses linear programming to estimate the efficiency of multiple decision-making units and it is commonly used in production, management and economics [3]. dea generates an efficiency score between 0 and 1 for each unit...

data envelopment analysis (dea) as a non-parametric method for efficiency measurement allows decision making units (dmus) to select the most advantageous weight factors in order to maximize their efficiency scores.  in most practical applications of dea presented in the literature, the presented models assume that all inputs are fully desirable. however, in many real situations undesirable inpu...

background: during the last decades, the number of dentistry units increased significantly across the country. the aim of this study was to assess the efficiency of dental units of iran provinces regarding dental health inputs and outputs using data envelopment analysis approach. methods: in this applied descriptive-analytical study, the study population included all of iran 31 provinces. the o...