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2014
- handle: 10670/1.n4cv2k
- hal: hal-01474415
- doi: 10.1016/j.ejor.2014.01.002
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info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ejor.2014.01.002
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Glaydston Carvalho Bento et al., « The self regulation problem as an inexact steepest descent method for multicriteria optimization », HAL-SHS : économie et finance, ID : 10.1016/j.ejor.2014.01.002
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Résumé
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.