Abstract
Eliciting the preferences of a decision maker is a crucial step when applying multi-criteria decision aid methods on real applications. Yet it remains an open research question, especially in the context of the promethee methods. In this paper, we propose a bi-objective optimization model to tackle the preference elicitation problem. Its main advantage over the widely spread linear programming methods (traditionally proposed to address this question) is the simultaneous optimization of (1) the number of inconsistencies and (2) the robustness of the parameter values. We experimentally study our method for inferring the promethee II preference parameters using the NSGA-II evolutionary multi-objective optimization algorithm. Results obtained on artificial datasets suggest that our method offers promising new perspectives in that field of research.
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Eppe, S., De Smet, Y., Stützle, T. (2011). A Bi-objective Optimization Model to Eliciting Decision Maker’s Preferences for the PROMETHEE II Method. In: Brafman, R.I., Roberts, F.S., Tsoukiàs, A. (eds) Algorithmic Decision Theory. ADT 2011. Lecture Notes in Computer Science(), vol 6992. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24873-3_5
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DOI: https://doi.org/10.1007/978-3-642-24873-3_5
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