A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems
Optimization and Control
2020-12-18 v2
Abstract
In this article we propose a descent method for equality and inequality constrained multiobjective optimization problems (MOPs) which generalizes the steepest descent method for unconstrained MOPs by Fliege and Svaiter to constrained problems by using two active set strategies. Under some regularity assumptions on the problem, we show that accumulation points of our descent method satisfy a necessary condition for local Pareto optimality. Finally, we show the typical behavior of our method in a numerical example.
Cite
@article{arxiv.1712.03005,
title = {A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems},
author = {Bennet Gebken and Sebastian Peitz and Michael Dellnitz},
journal= {arXiv preprint arXiv:1712.03005},
year = {2020}
}