The self regulation problem as an inexact steepest descent method for multicriteria optimization |
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| Authors: | G.C. Bento J.X. Cruz Neto P.R. Oliveira A. Soubeyran |
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| Affiliation: | 1. IME, Universidade Federal de Goiás, Goiânia, GO 74001-970, Brazil;2. DM, Universidade Federal do Piauí, Teresina, PI 64049-500, Brazil;3. COPPE/Sistemas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ 21945-970, Brazil;4. GREQAM-AMSE, Aix-Marseille University, France |
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| 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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| Keywords: | Multiple objective programming Steepest descent Self regulation Quasi-convexity |
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