measuring efficiency using fuzzy dea and fuzzy constraints to control weights and to find a common set of weights

Ranking Two-Stage Process Using a Common Set of Weights in DEA

Supply chain management is the combination of art and science that goes into improving the supply chain. In some cases of supply chain especially two-stage process, differing weights for the same factors, may not acceptable. The purpose of this paper is a performance evaluation of two-stage using DEA and based on a CSW model and this method for ranking two-stage and could be used to measure the...

Determining a common set of weights in DEA by solving a linear programming

In models of Data Envelopment Analysis (DEA), an optimal set of input and output weights is generally as-sumed to represent the assessed Decision Making Unit (DMU) in the best light in comparison to all the other DMUs. These sets of weights are, typically, different for each of the participating DMUs. Thus, it is important to find a Common Set of Weights (CSW) across the set of DMUs. In this pa...

Deriving Common Set of Weights in the Presence of the Undesirable Inputs: A DEA based Approach

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...

DEA common set of weights based on a multi objective Fractional Programming

Data envelopment analysis operates as a tool for appraising the relative efficiency of a set of homogenous decision making units. This methodology is applied widely in different contexts. Regarding to its logic, DEA allows each DMU to take its optimal weight in comparison with other DMUs while a similar condition is considered for other units. This feature is a bilabial characteri...

Finding a Common Set of Weights by the Fuzzy Entropy Compared with Data Envelopment Analysis - A Case Study

  A data envelopment analysis (DEA) method can be regarded as a useful management tool to evaluate decision making units (DMUs) using multiple inputs and outputs. In some cases, we face with imprecise inputs and outputs, such as fuzzy or interval data, so the efficiency of DMUs will not be exact. Most researchers have been interested in getting efficiency and ranking DMUs recently. Models of th...

Using DEA to compute most favourable and least favourable sets of weights in ABC inventory classification