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Communication Dans Un Congrès Année : 2019

BiOWA for Preference Aggregation with Bipolar Scales: Application to Fair Optimization in Combinatorial Domains

Hugo Martin
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Patrice Perny

Résumé

We study the biOWA model for preference aggregation and multicriteria decision making from bipolar rating scales. A biOWA is an ordered doubly weighted averaging extending standard ordered weighted averaging (OWA) and allowing a finer control of the importance attached to positive and negative evaluations in the aggregation. After establishing some useful properties of biOWA to generate balanced Pareto-optimal solutions, we address fair biOWA-optimization problems in com-binatorial domains. We first consider the use of biOWA in multi-winner elections for aggregating graded approval and disapproval judgements. Then we consider the use of biOWA for solving robust path problems with costs expressing gains and losses. A linearization of biOWA is proposed, allowing both problems to be solved by MIP. A path-ranking algorithm for biOWA optimization is also proposed. Numerical tests are provided to show the practical efficiency of our models.
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Dates et versions

hal-02862170 , version 1 (14-12-2020)

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Hugo Martin, Patrice Perny. BiOWA for Preference Aggregation with Bipolar Scales: Application to Fair Optimization in Combinatorial Domains. The 28th International Joint Conference on Artificial Intelligence (IJCAI'19), Aug 2019, Macao, China. pp.1822-1828, ⟨10.24963/ijcai.2019/252⟩. ⟨hal-02862170⟩
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