Supporting the multi-criteria decision aiding process: R and the MCDA package

Sébastien Bigaret, Richard E. Hodgett, Patrick Meyer (), Tatiana Mironova and Alexandru-Liviu Olteanu
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Sébastien Bigaret: IMT Atlantique, Lab-STICC, Univ. Bretagne Loire
Richard E. Hodgett: The University of Leeds
Patrick Meyer: IMT Atlantique, Lab-STICC, Univ. Bretagne Loire
Tatiana Mironova: IMT Atlantique, Lab-STICC, Univ. Bretagne Loire
Alexandru-Liviu Olteanu: IMT Atlantique, Lab-STICC, Univ. Bretagne Loire

EURO Journal on Decision Processes, 2017, vol. 5, issue 1, No 9, 169-194

Abstract: Abstract Reaching a decision when multiple, possibly conflicting, criteria are taken into account is often a difficult task. This normally requires the intervention of an analyst to aid the decision maker in following a clear methodology with respect to the steps that need to be taken, as well as the use of different algorithms and software tools. Most of these tools focus on one or a small number of algorithms, some are difficult to adapt and interface with other tools, while only a few belong to dynamic communities of contributors allowing them to expand in use and functionality. In this paper, we address these issues by proposing to use the R statistical environment and the MCDA package of decision aiding algorithms and tools. This package is meant to provide a wide range of MCDA algorithms that may be used by an analyst to tailor a decision aiding process to their needs, while the choice of R takes advantage of the yet poorly explored opportunity to interface data analysis and decision aiding. We additionally demonstrate the use of this tool on a practical application following a well-defined decision aiding process.

Keywords: R; MCDA; Decision aiding process; 90; 68 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s40070-017-0064-1

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