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Journal Articles Annals of Operations Research Year : 2022

Pareto solutions as limits of collective traps: an inexact multiobjective proximal point algorithm

Abstract

In this paper we introduce a definition of approximate Pareto efficient solution as well as a necessary condition for such solutions in the multiobjective setting on Riemannian manifolds. We also propose an inexact proximal point method for nonsmooth multiobjective optimization in the Riemannian context by using the notion of approximate solution. The main convergence result ensures that each cluster point (if any) of any sequence generated by the method is a Pareto critical point. Furthermore, when the problem is convex on a Hadamard manifold, full convergence of the method for a weak Pareto efficient solution is obtained. As an application, we show how a Pareto critical point can be reached as a limit of traps in the context of the variational rationality approach of stay and change human dynamics.
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Dates and versions

hal-03680291 , version 1 (13-02-2023)

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Glaydston Carvalho Bento, João Xavier da Cruz Neto, L. Meireles, Antoine Soubeyran. Pareto solutions as limits of collective traps: an inexact multiobjective proximal point algorithm. Annals of Operations Research, 2022, 316 (2), pp.1425-1443. ⟨10.1007/s10479-022-04719-y⟩. ⟨hal-03680291⟩
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