Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF

The present research work deals with a logistic membership function (MF), within non-linear MFs, in finding out fuzziness patterns in disparate level of satisfaction for Multiple Criteria Decision-Making (MCDM) problem. This MF is a modified form of general set of S-curve MF. Flexibility of this MF...

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Main Authors: P., Vasant, A., Bhattacharya, B., Sarkar, S.K., Mukherjee
Format: Citation Index Journal
Language:English
Published: 2007
Subjects:
Online Access:http://scholars.utp.edu.my/id/eprint/407/
http://scholars.utp.edu.my/id/eprint/407/1/paper.pdf
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author P., Vasant
A., Bhattacharya
B., Sarkar
S.K., Mukherjee
author_facet P., Vasant
A., Bhattacharya
B., Sarkar
S.K., Mukherjee
author_sort P., Vasant
building UTP Institutional Repository
collection Online Access
description The present research work deals with a logistic membership function (MF), within non-linear MFs, in finding out fuzziness patterns in disparate level of satisfaction for Multiple Criteria Decision-Making (MCDM) problem. This MF is a modified form of general set of S-curve MF. Flexibility of this MF in applying to real world problem has also been validated through a detailed analysis. An example illustrating an MCDM model applied in an industrial engineering problem has been considered to demonstrate the veracity of the proposed technique. 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 paper is to guide decision makers in finding out the best candidate-alternative with higher degree of satisfaction with lesser degree of vagueness under tripartite fuzzy environment. © 2006 Elsevier B.V. All rights reserved.
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spelling oai:scholars.utp.edu.my:4072017-01-19T08:27:12Z http://scholars.utp.edu.my/id/eprint/407/ Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF P., Vasant A., Bhattacharya B., Sarkar S.K., Mukherjee TK Electrical engineering. Electronics Nuclear engineering The present research work deals with a logistic membership function (MF), within non-linear MFs, in finding out fuzziness patterns in disparate level of satisfaction for Multiple Criteria Decision-Making (MCDM) problem. This MF is a modified form of general set of S-curve MF. Flexibility of this MF in applying to real world problem has also been validated through a detailed analysis. An example illustrating an MCDM model applied in an industrial engineering problem has been considered to demonstrate the veracity of the proposed technique. 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 paper is to guide decision makers in finding out the best candidate-alternative with higher degree of satisfaction with lesser degree of vagueness under tripartite fuzzy environment. © 2006 Elsevier B.V. All rights reserved. 2007 Citation Index Journal PeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/407/1/paper.pdf P., Vasant and A., Bhattacharya and B., Sarkar and S.K., Mukherjee (2007) Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF. [Citation Index Journal] http://www.scopus.com/inward/record.url?eid=2-s2.0-34147219565&partnerID=40&md5=78e2953f511318f5a87a53b814604161 10.1016/j.asoc.2006.10.005 10.1016/j.asoc.2006.10.005 10.1016/j.asoc.2006.10.005
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
P., Vasant
A., Bhattacharya
B., Sarkar
S.K., Mukherjee
Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF
title Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF
title_full Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF
title_fullStr Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF
title_full_unstemmed Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF
title_short Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF
title_sort detection of level of satisfaction and fuzziness patterns for mcdm model with modified flexible s-curve mf
topic TK Electrical engineering. Electronics Nuclear engineering
url http://scholars.utp.edu.my/id/eprint/407/
http://scholars.utp.edu.my/id/eprint/407/
http://scholars.utp.edu.my/id/eprint/407/
http://scholars.utp.edu.my/id/eprint/407/1/paper.pdf