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The self regulation problem as an inexact steepest descent method for multicriteria optimization

Abstract : In this paper we study an inexact steepest descent method for multicriteria optimization whose step-size comes with Armijo's rule. We show that this method is well-defined. Moreover, by assuming the quasi-convexity of the multicriteria function, we prove full convergence of any generated sequence to a Pareto critical point. As an application, we offer a model for the Psychology's self regulation problem, using a recent variational rationality approach.
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https://hal-amu.archives-ouvertes.fr/hal-01474415
Contributor : Elisabeth Lhuillier <>
Submitted on : Wednesday, February 22, 2017 - 5:24:47 PM
Last modification on : Wednesday, August 5, 2020 - 3:18:24 AM

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Glaydston Carvalho Bento, Joao Xavier Neto, Paulo Roberto Oliveira, Antoine Soubeyran. The self regulation problem as an inexact steepest descent method for multicriteria optimization. European Journal of Operational Research, Elsevier, 2014, 235 (3), pp.494--502. ⟨10.1016/j.ejor.2014.01.002⟩. ⟨hal-01474415⟩

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