2014•Unpublished venueOpen access

A Multiple Criteria Decision Analysis (MCDA) Software Selection Framework

Li Yan, Manoj Abraham Thomas

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Abstract

With the gaining popularity of multiple criteria decision analysis (MCDA) among researchers and practitioners, a variety of software that implements sophisticated MCDA methods and techniques is now available. To address the issue of the missing methodological approach in MCDA software selection, especially the mismatch between the decision making situation (DMS) structuring and the preference structuring employed by the tools, we propose a framework to enable the decision maker to choose relevant MCDA software. This is the first attempt to formally model the MCDA software selection process. A comprehensive set of MCDA methods meta-data for software selection is identified and demonstrated using the example of a specific DMS.

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What this paper is about

With the gaining popularity of multiple criteria decision analysis (MCDA) among researchers and practitioners, a variety of software that implements sophisticated MCDA methods and techniques is now available. To address the issue of the missing methodological approach in MCDA software selection, especially the mismatch between the decision making situation (DMS) structuring and the preference structuring employed by the tools, we propose a framework to enable the decision maker to choose relevant MCDA software. This is the first attempt to formally model the MCDA software selection process. A comprehensive set of MCDA methods meta-data for software selection is identified and demonstrated using the example of a specific DMS.

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Available abstract

With the gaining popularity of multiple criteria decision analysis (MCDA) among researchers and practitioners, a variety of software that implements sophisticated MCDA methods and techniques is now available. To address the issue of the missing methodological approach in MCDA software selection, especially the mismatch between the decision making situation (DMS) structuring and the preference structuring employed by the tools, we propose a framework to enable the decision maker to choose relevant MCDA software. This is the first attempt to formally model the MCDA software selection process. A comprehensive set of MCDA methods meta-data for software selection is identified and demonstrated using the example of a specific DMS.

Key concepts: Multiple-criteria decision analysis, Structuring, Computer science, Selection (genetic algorithm), Software, Decision analysis, Management science, Data mining

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