The problem of utilizing undesirable (bad) outputs in DEA models often need replacing the assumption of free disposability of outputs by weak disposability of outputs. The Kuosmanen technology is the only correct representation of the fully convex technology exhibiting weak disposability of bad and good outputs. Also, there are some specific features of non-radial data envelopment analysis (DEA...

Binaural Cue Coding (BCC) is a method for multichannel spatial rendering based on one down-mixed audio channel and BCC side information. The BCC side information has a low data rate and it is derived from the multichannel encoder input signal. A natural application of BCC is multichannel audio data rate reduction since only a single down-mixed audio channel needs to be transmitted. An alternati...

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.

We develop comparative results for ratio-based efficiency analysis (REA), based on the decision making units’ (DMUs’) relative efficiencies over sets of feasible weights that characterize preferences for input and output variables. Specifically, we determine (i) ranking intervals which indicate the best and worst efficiency rankings that a DMU can attain relative to other DMUs, (ii) dominance r...

Performance measurement of Decision Making Units (DMU) possessing an array positive and negative type input output data has been extensively researched topic in Data Envelopment Analysis. However, assessment Returns to Scale (RTS) under problem only attainable after the deliberation a Variable assumption. Steps referred earlier were indeed purported solution around vicinity Unit examination pre...

Data envelopment analysis (DEA) is the leading technique for assessing the efficiency of decision making units (DMU) in the presence of multiple inputs and outputs. The two milestone DEA models, namely the CCR (Charnes et al., 1978) and the BCC (Banker et al., 1984) models have become standards in the literature of performance measurement. Recent applications of DEA include, among others, those...

Data envelopment analysis (DEA) measures relative efficiency among the decision making units (DMU) without considering noise in data. The least efficient DMU indicates that it is in the worst situation. In this paper, we measure efficiency of individual DMU whenever it losses the maximum output, and the efficiency of other DMUs is measured in the observed situation. This efficiency is the minim...

In models of data envelopment analysis (DEA), an optimal set of weights is generally assumed to represent the assessed decision making unit(DMU) in the best light in comparison to all the other DMUs, and so there is an optimal set of weights corresponding to each DMU. The present paper, proposes a three stage method to determine one common set of weights for decision making units. Then, we use ...

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...

  In this paper, presenting two simple methods for ranking of efficient DMUs in DEA models that included to add one virtual DMU as ideal DMU and is using the additive model. Note that, we use an ideal point just for comparing efficient DMUs with. Although these methods are simple, they have ability for ranking all efficient DMUs, extreme points and the others, also they are capable of ranking t...