Sensing degree of fuzziness in MCDM model using modified flexible S-curve MF
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 incomme...
| Main Authors: | , |
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| Format: | Citation Index Journal |
| Language: | English |
| Published: |
2007
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| Subjects: | |
| Online Access: | http://scholars.utp.edu.my/id/eprint/413/ http://scholars.utp.edu.my/id/eprint/413/1/paper.pdf |
| _version_ | 1848658979250503680 |
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| author | P., Vasant A., Bhattacharya |
| author_facet | P., Vasant A., Bhattacharya |
| author_sort | P., Vasant |
| building | UTP Institutional Repository |
| collection | Online Access |
| 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.
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| first_indexed | 2025-11-13T07:23:08Z |
| format | Citation Index Journal |
| id | oai:scholars.utp.edu.my:413 |
| institution | Universiti Teknologi Petronas |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-13T07:23:08Z |
| publishDate | 2007 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:scholars.utp.edu.my:4132017-01-19T08:27:12Z http://scholars.utp.edu.my/id/eprint/413/ Sensing degree of fuzziness in MCDM model using modified flexible S-curve MF P., Vasant A., Bhattacharya TK Electrical engineering. Electronics Nuclear engineering 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. 2007 Citation Index Journal PeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/413/1/paper.pdf P., Vasant and A., Bhattacharya (2007) Sensing degree of fuzziness in MCDM model using modified flexible S-curve MF. [Citation Index Journal] http://www.scopus.com/inward/record.url?eid=2-s2.0-34250875093&partnerID=40&md5=7500d030561c6868b82eabedcef742f2 10.1080/00207720601117108 10.1080/00207720601117108 10.1080/00207720601117108 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering P., Vasant A., Bhattacharya Sensing degree of fuzziness in MCDM model using modified flexible S-curve MF |
| title | Sensing degree of fuzziness in MCDM model using modified flexible S-curve MF
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| title_full | Sensing degree of fuzziness in MCDM model using modified flexible S-curve MF
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| title_fullStr | Sensing degree of fuzziness in MCDM model using modified flexible S-curve MF
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| title_full_unstemmed | Sensing degree of fuzziness in MCDM model using modified flexible S-curve MF
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| title_short | Sensing degree of fuzziness in MCDM model using modified flexible S-curve MF
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| title_sort | sensing degree of fuzziness in mcdm model using modified flexible s-curve mf |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://scholars.utp.edu.my/id/eprint/413/ http://scholars.utp.edu.my/id/eprint/413/ http://scholars.utp.edu.my/id/eprint/413/ http://scholars.utp.edu.my/id/eprint/413/1/paper.pdf |