DocumentCode
1853638
Title
Data envelopment analysis using fuzzy concept
Author
Kahraman, Cengiz ; Tolga, Ethem
Author_Institution
Dept. of Ind. Eng., Istanbul Tech. Univ., Turkey
fYear
1998
fDate
27-29 May 1998
Firstpage
338
Lastpage
343
Abstract
Mathematical programming is one of the areas to which fuzzy set theory has been applied extensively. Primarily based on Bellman and Zadeh´s model of decision in fuzzy environments, models have been suggested which allow flexibility in constraints and nonlinear programming. Data envelopment analysis (DEA) is a method of evaluating relative efficiencies for a group of similar units based on an efficiency concept. In DEA, the same set of factors is measured for each unit, and there are multiple and non-commensurate inputs and outputs. Efficiency is measured as the weighted sum of output over the weighted sum of input. This is the DEA ratio model. The other models are radial models, additive models, multiplicative models, hyperbolic models, nonradial models. In this paper, assuming that the values of inputs and outputs in DEA are nor known with certainty, a fuzzy mathematical programming is proposed. The objective function and the constraints are represented by using their degrees of membership in DEA. The main advantage of this solution that the decision maker is nor forced into a precise formulation for mathematical reasons
Keywords
fuzzy set theory; mathematical programming; DEA ratio model; constraints; data envelopment analysis; degrees of membership; fuzzy concept; fuzzy set theory; mathematical programming; objective function; Data envelopment analysis; Electronic mail; Fuzzy logic; Fuzzy set theory; Industrial engineering; Linear programming; Logic design; Logic devices; Logic programming; Mathematical programming;
fLanguage
English
Publisher
ieee
Conference_Titel
Multiple-Valued Logic, 1998. Proceedings. 1998 28th IEEE International Symposium on
Conference_Location
Fukuoka
ISSN
0195-623X
Print_ISBN
0-8186-8371-6
Type
conf
DOI
10.1109/ISMVL.1998.679511
Filename
679511
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