The self regulation problem as an inexact steepest descent method for multicriteria optimization
Provides a theoretical convergence result for multicriteria optimization with potential application to psychological self-regulation models, but the contribution is primarily theoretical and incremental.
The paper studies an inexact steepest descent method with Armijo's rule for multicriteria optimization, proving convergence to a critical Pareto point under quasi-convexity, and applies it to model self regulation in psychology.
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.