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...

In the existing DEA models, we have a centralized decision maker (DM) who supervises all the operating units. In this paper, we solve a problem in which the centralized DM encounters limited or constant resources for total inputs or total outputs. We establish a DEA target model that solves and deals with such a situation. In our model, we consider the decrease of total input consumption and th...

over the years we have witnessed the growing importance of supply chain operations and supply chain management (scm), as supply chains play a major role in every step of the product life cycle. therefore, this paper will dea-based performance evaluation approaches for overall supply chain can be categorized. future perspectives and challenges are discussed

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...

In original Data Envelopment Analysis (DEA) models for measuring the relative efficiencies of a set of Decision Making Units (DMUs) using various inputs to produce various outputs are limited to crisp data. To deal with imprecise data, the notion of fuzziness has been introduced. this paper develops a procedure to measure the efficiencies of DMUs with fuzzy observations. The basic idea is to tr...

In this paper, we reformulate the conventional DEA models as an imprecise problem and propose a novel method for evaluating DMUs when inputs outputs are fuzzy and/or ordinal or vary in intervals. For purpose, convert all data into interval data. order to each number data, use nearest weighted approximation of numbers by applying weighting function, one. manner, could The presented determine eff...