Sensing degree of fuzziness in MCDM model using modified flexible S -curve MF

Vasant, Pandian and Bhattacharya, Arijit (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 0020-7721

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Abstract

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.

Item Type: Article
Faculty \ School: Faculty of Social Sciences > Norwich Business School
Depositing User: LivePure Connector
Date Deposited: 25 Oct 2019 08:30
Last Modified: 22 Apr 2020 08:18
URI: https://ueaeprints.uea.ac.uk/id/eprint/72775
DOI: 10.1080/00207720601117108

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