data envelopment analysis (dea) is a nonparametric technique that includes models to evaluate the relative efficiency of decision making units (dmus). it has the ability to separate efficient units and inefficient units. one of the applications of this mathematical technique is evaluating performance of supply chain. according to such as the inefficiency factors of one dmu, is existence congest...

sohrabi and nalchigar (2010) proposed a new data envelopment analysis (dea) model to identify the most efficient decision-making unit (dmu) in presence of imprecise data. in this paper, it is shown that the proposed model is not able to determine the most efficient dmu and is randomly introduced an efficient dmu. in addition, it is shown that this model determines the most efficient dmu in the ...

This paper gives a new application of DEA to evaluate the scheduling solutions of parallel processing. It evaluates the scheduling solutions of parallel processing using the non-convex DEA model, FDH model. By introducing each solution of parallel processing scheduling as a DMU with some relevant inputs and outputs this paper shows that how the most efficient schedule(s) can be identified.

Data envelopment analysis (DEA) is a method frequently used to evaluate relative firm performance. However, high values in a few indicators can lead to a company being regarded as ‘efficient’, despite valuing poorly in other essential indicators. The Inefficiency Countervailed DEA (IC-DEA) method is thus developed. The method first defines an inefficient frontier using the proposed Reverse DEA ...

Data envelopment analysis (DEA) is a representative method to estimate efficient frontiers and derive efficiency. However, in a situation with weight restrictions on individual input–output pairs, its suitability has been questioned. Therefore, the main purpose of this paper is to develop a mathematical method, which we call the input-oriented ratio-based comparative efficiency model, DEA-R-I, ...

In the data envelopment analysis (DEA) literature, linear fractional non-cooperative network DEA models for two-stage network structures are often transformed into parametric linear models. The transformed parametric linear models are then solved by computing a series of linear models when the parameter is varied. For example, Wu, Zhu, Ji, Chu and Liang (2016) provide a linear fractional non-co...

A dual-band artificial magnetic material and then a dual-band double-negative metamaterial structure based on symmetric spiral resonators are presented. An approximate analytical model is used for the initial design of the proposed structures. The electromagnetic parameters of the proposed metamaterial structure retrieved using an advanced parameter retrieval method based on the causality princ...