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Inexact Multi-Objective Local Search Proximal Algorithms: Application to Group Dynamic and Distributive Justice Problems

Abstract : We introduce and examine an inexact multi-objective proximal method with a proximal distance as the perturbation term. Our algorithm utilizes a local search descent process that eventually reaches a weak Pareto optimum of a multi-objective function, whose components are the maxima of continuously differentiable functions. Our algorithm gives a new formulation and resolution of the following important distributive justice problem in the context of group dynamics: In each period, if a group creates a cake, the problem is, for each member, to get a high enough share of this cake; if this is not possible, then it is better to quit, breaking the stability of the group.
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https://hal-amu.archives-ouvertes.fr/hal-01985329
Contributor : Elisabeth Lhuillier <>
Submitted on : Thursday, January 17, 2019 - 7:29:21 PM
Last modification on : Wednesday, August 5, 2020 - 3:13:45 AM

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Glaydston de Carvalho Bento, Orizon Pereira Ferreira, Antoine Soubeyran, Valdinês Leite De Sousa Júnior. Inexact Multi-Objective Local Search Proximal Algorithms: Application to Group Dynamic and Distributive Justice Problems. Journal of Optimization Theory and Applications, Springer Verlag, 2018, 177 (1), pp.181-200. ⟨10.1007/s10957-018-1258-9⟩. ⟨hal-01985329⟩

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