A new approach for choosing the most appropriate fuzzy ranking algorithm for solving madm problems

Ramezani, F; Lu, J

A new approach for choosing the most appropriate fuzzy ranking algorithm for solving madm problems

Ramezani, F

Lu, J

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Publication Type:: Conference Proceeding
Citation:: Studies in Computational Intelligence, 2011, 391 pp. 13 - 24
Issue Date:: 2011-12-01

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Field	Value	Language
dc.contributor.author	Ramezani, F https://orcid.org/0000-0002-0368-321X	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.date.issued	2011-12-01	en_US
dc.identifier.citation	Studies in Computational Intelligence, 2011, 391 pp. 13 - 24	en_US
dc.identifier.isbn	9783642248054	en_US
dc.identifier.issn	1860-949X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/19121
dc.description.abstract	There are many fuzzy ranking algorithms available to solve multi-attribute decision making (MADM) problems. Some are more suitable than others for particular decision problems. This paper proposes a new method for choosing the most appropriate fuzzy ranking algorithm for solving MADM problems based on the type and number of attributes and the number of alternatives, considering the least time consumption and the least computation for ranking alternatives. In addition, we develop a software to simulate three main fuzzy ranking algorithms: SAW, Negi, and Chen and Hwang (Chen and Hwang 1992). This software can be used in any MADM decision support system.	en_US
dc.relation.ispartof	Studies in Computational Intelligence	en_US
dc.relation.isbasedon	10.1007/978-3-642-24806-1_2	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	A new approach for choosing the most appropriate fuzzy ranking algorithm for solving madm problems	en_US
dc.type	Conference Proceeding
utslib.citation.volume	391	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Mallorca, Spain	en_US
dc.location.activity	Boston, MA
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	391	en_US

Abstract:

There are many fuzzy ranking algorithms available to solve multi-attribute decision making (MADM) problems. Some are more suitable than others for particular decision problems. This paper proposes a new method for choosing the most appropriate fuzzy ranking algorithm for solving MADM problems based on the type and number of attributes and the number of alternatives, considering the least time consumption and the least computation for ranking alternatives. In addition, we develop a software to simulate three main fuzzy ranking algorithms: SAW, Negi, and Chen and Hwang (Chen and Hwang 1992). This software can be used in any MADM decision support system.

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http://hdl.handle.net/10453/19121