Rank similarity based MADM method selection

Chakraborty, Subrata and Yeh, Chung-Hsing (2012) Rank similarity based MADM method selection. In: 2012 International Conference on Statistics in Science, Business, and Engineering, 10-12 Sept 2012, Langkawi, Malaysia.


Selecting the most suitable Multiple Attribute Decision Making (MADM) method for a given MADM problem is a challenge for the decision maker. When there are several suitable MADM methods available for the problem, the challenge is even greater. We present a novel MADM method selection approach based on the Spearman's rank correlation. The approach will help the decision maker in selecting the most preferred MADM method from a set of suitable and acceptable methods. The most preferred MADM method is the one that produces the most preferred outcome. The most preferred outcome is the one which is closest to all other outcomes. The closeness between the ranking outcomes are measured in terms of the similarity between them.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Faculty/School / Institute/Centre: Historic - Faculty of Business and Law - School of Management and Marketing (1 Jan 2011 - 30 Jun 2013)
Faculty/School / Institute/Centre: Historic - Faculty of Business and Law - School of Management and Marketing (1 Jan 2011 - 30 Jun 2013)
Date Deposited: 24 May 2016 06:00
Last Modified: 15 Aug 2017 00:51
Uncontrolled Keywords: Spearman rank correlation; multiple attribute decision making; rank similarity based MADM method selection
Fields of Research (2008): 08 Information and Computing Sciences > 0806 Information Systems > 080605 Decision Support and Group Support Systems
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4609 Information systems > 460902 Decision support and group support systems
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: https://doi.org/10.1109/ICSSBE.2012.6396586
URI: http://eprints.usq.edu.au/id/eprint/27918

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