Supplier selection is a multi-Criteria problem. This study proposes a hybrid model for supporting the suppliers’ selection and ranking. This research is a two-stage model designed to fully rank the suppliers where each supplier has multiple Inputs and Outputs. First, the supplier evaluation problem is formulated by Data Envelopment Analysis (DEA), since the regarded decision deals with uncertai...

in this study, the relative performance of mazandaran wood and paper company as a major supplier of paper products in iran was measured. network data envelopment analysis (dea) models with parallel structure were used to evaluate and measure its performance. gams software version 23.4 was used for data analysis. results indicated that this company in all studied years had good performances base...

This short communication complements the DEA model proposed by Lovell and Pastor (Eur. J. Oper. Res. 118 (1999), 46-51), by incorporating both positive and negative criteria in the model. As such, we propose a DEA model, known as pure DEA, using a directional distance function approach.

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 ...

Proposed in this study is a hybrid model for supporting the performance of a department within Amir Kabir University in Iran. The proposal is a two-stage model designed to fully rank the organizational departments where each faculty has multiple inputs and outputs. First, the Data Envelopment Analysis (DEA) separately formulates each pair of units. In the second stage, the pair-wise evaluation ...

Data envelopment analysis (DEA) is a well-Known method in efficiency evaluation of a set of decision making units (DMUs) such as organizations and banks. An advantage of DEA technique is selection of weights at random. Weight selection is of crucial importance in efficiency evaluation. In this regard, it is important to employ models that have more freedom in selecting weights. One such model i...

data envelopment analysis (dea) models with interval inputs and outputs have been rarely discussed in dea literature. this paper, using the enhanced russell measurement proposes an extended model which permits the presence of interval scale variables which can take both negative and positive values. the model is compared with most well-known dea models of which include the ccr model, the bcc mo...

An original data envelopment analysis (DEA) model is to evaluate each decision-making unit (DMU) with a set of most favorable weights of performance indices. The efficient DMUs obtained from the original DEA construct an efficient (bestpractice) frontier. The original DEA can be considered to identify good (efficient) performers in the most favorable scenario. For the purpose of identifying bad...

This paper processes a unification of Fuzzy TOPSIS and Data Envelopment Analysis DEA to select the units with most efficiency. This research is a two-stage model designed to fully rank the organizational alternatives, where each alternative has multiple inputs and outputs. First, the alternative evaluation problem is formulated byData Envelopment Analysis DEA and separately formulates each pair...