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

G.C. Bento, J.X. Cruz Neto, P.R. Oliveira and Antoine Soubeyran

European Journal of Operational Research, 2014, vol. 235, issue 3, 494-502

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.

Keywords: Multiple objective programming; Steepest descent; Self regulation; Quasi-convexity (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (7)

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Working Paper: The self regulation problem as an inexact steepest descent method for multicriteria optimization (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:235:y:2014:i:3:p:494-502

DOI: 10.1016/j.ejor.2014.01.002

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