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...

In many data envelopment analysis (DEA) applications, the analyst always confronts the difficulty that the selected data set is not suitable to apply traditional DEA models for their poor discrimination. This paper presents an approach using Shannon’s entropy to improve the discrimination of traditional DEA models. In this approach, DEA efficiencies are first calculated for all possible variabl...

This paper concentrates on methods for comparing activity units found relatively efficient by data envelopment analysis (DEA). The use of the basic DEA models does not provide direct information regarding the performance of such units. The paper provides a systematic framework of alternative ways for ranking DEA-efficient units. The framework contains criteria derived as by-products of the basi...

data envelopment analysis (dea) is a non-parametric technique for evaluation of relative efficiency of decision making units described by multiple inputs and outputs. it is based on solving linear programming problems. since 1978 when basic dea model was introduced many its modifications were formulated. among them are two or multi-stage models with serial or parallel structure often called net...

The paper deals with models and methods for evaluation of efficiency of production units. The standard modeling approach for evaluation of efficiency is data envelopment analysis (DEA) based on the definition of efficiency as the ratio of outputs produced by the unit and inputs spent in the production process. Standard data envelopment analysis models divide the units into inefficient and effic...

The portfolio is a perfect combination of stock or assets, which an investor buys them. The objective of the portfolio is to divide the investment risk among several shares. Using non-parametric DEA and DEA-R methods can be of great significance in estimating portfolio. In the present paper, the efficient portfolio is estimated by using non-radial DEA and DEA-R models. By proposing non-radial m...

Data envelopment analysis (DEA) is a non-parametric method for evaluating the relative efficiency of decision making units (DMUs) on the basis of multiple inputs and outputs. The context-dependent DEA is introduced to measure the relative attractiveness of a particular DMU when compared to others. In real-world situation, because of incomplete or non-obtainable information, the data (Input and ...

This article integrates fuzzy set theory in Data Envelopment Analysis (DEA) framework to compute technical efficiency scores when input and output data are imprecise. In conventional DEA inputs and outputs data are precise. However, traffic and transportation take place in an uncertain environment and input and output data might be imprecise. This article proposes a possibility approach for sol...

One of the most popular approaches to measuring productivity changes is based on using Malmquist productivity indexes. In this paper we propose a method for obtaining interval Malmquist productivity index (IMPI). The classical DEA models have been before used for measuring the Malmquist productivity index. The current article extends DEA models for measuring the interval Malmquist productivity ...