Multiagent Fair Optimization with Lorenz Dominance
Galand, Lucie; Lust, Thibaut (2015), Multiagent Fair Optimization with Lorenz Dominance, in Bordini, Elkind; Weiss, Yolum, Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS 15), International Foundation for Autonomous Agents and Multiagent Systems : Richland, p. 1895-1896
TypeCommunication / Conférence
Conference titleInternational Conference on Autonomous Agents and Multiagent Systems (AAMAS 15)
Book titleProceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS 15)
Book authorBordini, Elkind; Weiss, Yolum
MetadataShow full item record
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Laboratoire d'Informatique de Paris 6 [LIP6]
Abstract (EN)This paper deals with fair optimization problems where several agents are involved. In this setting, a solution is evaluated by a vector whose components are the utility of the agents for this solution, and one looks for solutions that fairly satisfy all the agents. Lorenz dominance has been proposed in economics to refine the Pareto dominance by taking into account satisfaction inequality among the agents. The computation of Lorenz efficient solutions in multiagent optimization is however challenging (it has been shown intractable and NP-hard on certain problems). Nevertheless, to our knowledge, very few works address this problem. We propose thus in this work new methods to generate Lorenz efficient solutions. More precisely, we consider the adaptation of the well-known two-phase method proposed in biobjective optimization to the bi-agent optimization case, where one wants to directly compute the Lorenz efficient solutions. We study the efficiency of our method by applying it on the bi-agent knapsack problem.
Subjects / KeywordsMultiobjective combinatorial optimization; Fairness; Lorenz dominance; Two-phase method
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