The self regulation problem as an inexact steepest descent method for multicriteria optimization
Optimization and Control
2012-07-04 v1 Numerical Analysis
Abstract
In this paper, we study an inexact steepest descent method, with Armijo's rule, for multicriteria optimization. The sequence generated by the method is guaranteed to be well-defined. Assuming quasi-convexity of the multicriteria function we prove full convergence of the sequence to a critical Pareto point. As an application, this paper offers a model of self regulation in Psychology, using a recent variational rationality approach.
Cite
@article{arxiv.1207.0775,
title = {The self regulation problem as an inexact steepest descent method for multicriteria optimization},
author = {G. C. Bento and J. X. Cruz Neto and P. R. Oliveira and A. Soubeyran},
journal= {arXiv preprint arXiv:1207.0775},
year = {2012}
}
Comments
29 pages