fuzzy efficiency: multiplier and enveloping ccr ‎models‎

Authors

a. a. hosseinzadeh

f. hosseinzadeh lotfi

z. moghaddas

abstract

comparing the performance of a set of activities or organizations under uncertainty environment has been performed by means of fuzzy data envelopment analysis (fdea) since the traditional dea models require accurate and precise performance data. as regards a method for dealing with uncertainty environment, many researchers have introduced dea models in fuzzy environment. some of these models are solved by transforming fuzzy models into their crisp counterparts. in this paper applying a fuzzy metric and a ranking function, obtained from it, the multiplier fuzzy ccr model converts to its crisp counterpart. solving this model yields the optimal solution of fuzzy multiplier model. moreover, in the following some properties and theorems about mentioned enveloping and multiplier models have been ‎proved.‎

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

Fuzzy efficiency: Multiplier and enveloping CCR ‎models‎

Comparing the performance of a set of activities or organizations under uncertainty environment has been performed by means of Fuzzy Data Envelopment Analysis (FDEA) since the traditional DEA models require accurate and precise performance data. As regards a method for dealing with uncertainty environment, many researchers have introduced DEA models in fuzzy environment. Some of these models ar...

full text

Variable Frequency Multiplier Technique for High Efficiency

This paper presents a variable frequency multiplier technique (VFX) that enables design of converters for wide input and/or output voltage ranges while preserving high efficiency. The technique is applied to an LLC converter to demonstrate the effectiveness of this technique for converters having wide input voltage variation such as universal input power supplies. This technique compresses the ...

full text

The efficiency of Artificial Neural Network, Neuro-Fuzzy and Multivariate Regression models for runoff and erosion simulation using rainfall simulator

1- INTRODUCTION According to the complexity of environmental factors related to erosion and runoff, correct simulation of these variables find importance under rain intensity domain of watershed areas.  Although modeling of erosion and runoff by Artificial Neural Network and Neuro-Fuzzy based on rainfall-runoff and discharge-sediment models were widely applied by researchers, scrutinizing Arti...

full text

Optimal Growth Models and the Lagrange Multiplier∗

We provide sufficient conditions on the objective functional and the constraint functions under which the Lagrangean can be represented by a ` sequence of multipliers in infinite horizon discrete time optimal growth models.

full text

Centralized Cost Efficiency DEA Models

Cost efficiency measures the cost of resource by output production. While conventional cost efficiency models set targets separately for each DMU, There are cases where the Central decision making is seeking the above targets, and at the same tries to obtain the target of Min cost efficiency for the total consumption. in this paper we consider that there is a centralized decision maker (DM). In...

full text

Evaluation of the Neuro-Fuzzy and Hybrid Wavelet-Neural Models Efficiency in River Flow Forecasting (Case Study: Mohmmad Abad Watershed)

  One of the most important issues in watersheds management is rainfall-runoff hydrological process forecasting. Using new models in this field can contribute to proper management and planning. In addition, river flow forecasting, especially in flood conditions, will allow authorities to reduce the risk of flood damage. Considering the importance of river flow forecasting in water resources ma...

full text

My Resources

Save resource for easier access later


Journal title:
international journal of industrial mathematics

Publisher: science and research branch, islamic azad university, tehran, iran

ISSN 2008-5621

volume 8

issue 1 2016

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023