Inexact Multi-Objective Local Search Proximal Algorithms: Application to Group Dynamic and Distributive Justice Problems
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- handle: 10670/1.k1md7i
- hal: hal-01985329
- doi: 10.1007/s10957-018-1258-9
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info:eu-repo/semantics/altIdentifier/doi/10.1007/s10957-018-1258-9
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Glaydston de Carvalho Bento et al., « Inexact Multi-Objective Local Search Proximal Algorithms: Application to Group Dynamic and Distributive Justice Problems », HAL-SHS : économie et finance, ID : 10.1007/s10957-018-1258-9
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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.