Abstract
In this chapter, we illustrate how the MCDA process can be supported by the use of a decision aiding software called diviz. The diviz workbench allows to build, execute and share complex workflows of MCDA algorithms, and as such, is a convenient tool to help the analyst in the decision aiding process. We start by a presentation of diviz, before switching to the detailed description of a didactic MCDA process, based on a classical example from the MCDA literature. We show how each major step of this process can be backed up by diviz, and how the software can help to build the final recommendation.
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References
Bisdorff, R., Meyer, P., & Veneziano, T. (2009). Inverse analysis from a Condorcet robustness denotation of valued outranking relations. In F. Rossi, & A. Tsoukiàs (Eds.), Algorithmic decision theory. Lecture notes in artificial intelligence (Vol. 5783, pp. 180–191). Berlin: Springer.
Bouyssou, D., Marchant, T., Pirlot, M., Perny, P., Tsoukiàs, A., & Vincke, P. (2000). Evaluation and decision models: A critical perspective. Dordrecht: Kluwer.
Brans, J.-P., & Vincke, P. (1985). A preference ranking organization method. Management Science, 31(6), 647–656.
Decision Deck Consortium. (2009). Strategic manifesto of the Decision Deck project, http://www.decision-deck.org/manifesto.html.
Grabisch, M., Kojadinovic, I., & Meyer, P. (2008). A review of capacity identification methods for Choquet integral based multi-attribute utility theory; Applications of the Kappalab R package. European Journal of Operational Research, 186(2), 766–785. doi:10.1016/j.ejor.2007.02.025.
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I. H. (2009). The WEKA data mining software: An update. SIGKDD Explorations, 11(1), 10–18.
Jacquet-Lagrèze, E., & Siskos, Y. (1982). Assessing a set of additive utility functions for multicriteria decision making: The UTA method. European Journal of Operational Research, 10,151–164.
Meyer, P., & Bigaret, S. (2012). diviz: A software for modeling, processing and sharing algorithmic workflows in MCDA. Intelligent Decision Technologies, 6(4), 283–296. doi:10.3233/IDT-2012-0144.
R Development Core Team. (2005). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing, http://www.R-project.org [ISBN 3-900051-00-3].
Roy, B. (1968). Classement et choix en présence de points de vue multiples (la méthode ELECTRE). Revue française d’informatique et de recherche opérationnelle (RIRO), 2, 57–75.
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Bigaret, S., Meyer, P. (2015). Supporting the MCDA Process with the diviz workbench. In: Bisdorff, R., Dias, L., Meyer, P., Mousseau, V., Pirlot, M. (eds) Evaluation and Decision Models with Multiple Criteria. International Handbooks on Information Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46816-6_21
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DOI: https://doi.org/10.1007/978-3-662-46816-6_21
Publisher Name: Springer, Berlin, Heidelberg
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