‎in this paper, we present a two-stage model for ranking of decision making units (dmus) using interval analytic hierarchy process (ahp). since the efficiency score of unity is assigned to the efficient units, we evaluate the efficiency of each dmu by basic dea models and calculate the weights of the criteria using proposed model. in the first stage, the proposed model evaluates decision making...

in the present study, an attempt has been made to use data envelopment analysis (dea) for assessing the technical efficiency and return-to-scale for greenhouse cucumber production in iran. for this purpose, the data from greenhouses in esfahan province, during one period of plant cultivation in one year including spring plants were randomly collected. the results indicated that total input ener...

background: one way to improve the performance of hospitals, the largest resource-consuming units in the healthcare sector, is to continuously evaluate their performance.objective: the current study assessed the performance of hospitals affiliated with the kurdistan university of medical sciences using data envelopment analysis (dea).methods: this retrospective descriptive-analytic study used d...

background: nowadays, healthcare systems are considered as important service sectors, and they are social development and welfare standards; hence the performance of this sector is highly important. evaluating performance is the first step of various departments to determine the efficiency of the healthcare system. in the meantime, diagnostic laboratories of hospitals play important roles as sp...

Data Envelopment Analysis (DEA) is a widely used mathematical programming approach for evaluating the relative efficiency of Decision Making Units (DMUs). Conventional DEA methods treat DMUs as ‘‘black boxes’’, focusing entirely on their relative efficiencies. We propose an efficient two-stage fuzzy DEA model to calculate the efficiency scores for a DMU and its sub-DMUs. We use the Stackelberg ...

Data envelopment analysis (DEA) is a non-parametric technique to measure the efficiencies of a set of decision making units (DMUs) with common crisp inputs and outputs. In real-world problems, however, inputs and outputs typically have some levels of fuzziness. To analyze a DMU with fuzzy input/output data, previous studies provided the fuzzy DEA (FDEA) model and proposed an associated evaluati...

Data envelopment analysis (DEA) is a method to evaluate the efficiency of some decision making units which by using one or more inputs will make one or more outputs. In real world, most of the problems don’t have a certain mode. Fuzzy theory is one of the ways of considering uncertainty in the mathematical programming problems. In this study by using this idea, the DEA model on a fully fuzzy mo...

Data envelopment analysis (DEA) is a widely used mathematical programming approach for evaluating the relative efficiency of decision making units (DMUs) in organizations. Crisp input and output data are fundamentally indispensable in traditional DEA evaluation process. However, the input and output data in real-world problems are often imprecise or ambiguous. In this study, we present a four-p...

Abstract In contrast to classical data envelopment analysis (DEA), network DEA has attention the internal structure of a production system and reveals relationship between efficiency efficiencies processes. However, flexibility weights need for crisp input output in evaluation process are two major shortcomings models. This paper presents common approach relational model fuzzy environment measu...