relation: https://khub.utp.edu.my/scholars/283/
title: Sensing degree of fuzziness in MCDM model using modified flexible S-curve MF
creator: Vasant, P.
creator: Bhattacharya, A.
description: It is hard to sense the degree of vagueness while using a Multiple Criteria Decision-Making (MCDM) model in industrial engineering problems. Selection of best candidate-alternative is an important issue when the attributes of the candidate-alternatives are conflicting in nature and they have incommensurable units. An MCDM model makes it possible to select the candidate-alternative that suits best for the investor. An example illustrating an MCDM model applied in plant-site selection problem has been considered in this article to demonstrate the veracity of the proposed methodology. The degree of vagueness hidden in the proposed approach has been investigated using a flexible modified logistic membership function (MF). The approach presented here provides feedback to the decision maker, implementer and analyst and gives a clear indication about the appropriate application and usefulness of the MCDM model. The key objective of this article is to guide decision makers in finding out the best candidate-alternative with higher degree of satisfaction and lesser degree of vagueness.
date: 2007
type: Article
type: PeerReviewed
identifier:   Vasant, P. and Bhattacharya, A.  (2007) Sensing degree of fuzziness in MCDM model using modified flexible S-curve MF.  International Journal of Systems Science, 38 (4).  pp. 279-291.  ISSN 00207721     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-34250875093&doi=10.1080%2f00207720601117108&partnerID=40&md5=d3cdf8d9b10cf3860cb310a97b3c98f9
relation: 10.1080/00207720601117108
identifier: 10.1080/00207720601117108