Value-for-money is a widely used criterion to locate “best-buys” in a market of competitive products or services. The term “value” represents a composite measure of what a consumer gets from a product or service, while the term “money” is what the consumer pays for it. In the absence of individual preferences, the problem of identifying best-buys by the value-for-money criterion can be formulat...

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...

data envelopment analysis (dea) is a mathematical programming-based approach for evaluates the relative efficiency of a set of dmus (decision making units). the relative efficiency of a dmu is the result of comparing the inputs and outputs of the dmu and those of other dmus in the pps (production possibility set). also, in data envelopment analysis various models have been developed in order to...

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...

This paper suggests a method of finding super-efficiency scores and modification of input-oriented models for sensitivity analysis of decision making units. First, by using DEA-R (ratiobased DEA) models in the input orientation, the models of superefficiency and also models of super-efficiency modification are suggested. Second, the worst-case scenarios are considered where the efficiency of th...

data envelope analysis (dea) is an approach to estimate the relative efficiency of decision making units (dmus). several studies were conducted in order to prioritize efficient units and some useful models such as cross-efficiency matrix (cem) were presented.  besides, a number of dea models with interval data have been developed and ranking dmus with such data was solved. however, presenting a...

Amiodarone (AMD)-induced pulmonary toxicity (AIPT) is the most life-threatening side-effect of AMD treatment. N-Monodesethylamiodarone (DEA), an active metabolite of AMD, also exhibits cytotoxicity and tends to accumulate in the lung more intensively than AMD. In this study, we characterized the mechanism of DEA accumulation using A549 cells as a model of the alveolar epithelium. Typical ATP-de...

Although crisp data are fundamentally indispensable for determining the profit Malmquist productivity index (MPI), the observed values in real-world problems are often imprecise or vague. These imprecise or vague data can be suitably characterized with fuzzy and interval methods. In this paper, we reformulate the conventional profit MPI problem as an imprecise data envelopment analysis (DEA) pr...

Risk early-warning of natural disasters is a very intricate non-deterministic prediction, and it was difficult to resolve the conflicts and incompatibility of the risk structure. Risk early-warning factors of natural disasters were differentiated into essential attributes and external characters, and its workflow mode was established on risk early-warning structure with integrated Entropy and D...

on account of the existence of uncertainty, dea occasionally faces the situation of imprecise data, especially when a set of dmus include missing data, ordinal data, interval data, stochastic data, or fuzzy data. therefore, how to evaluate the efficiency of a set of dmus in interval environments is a problem worth studying. in this paper, we discussed the new method for evaluation and ranking i...