An interior point method for nonlinear constrained derivative-free optimization

Fuente: arXiv
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Autori principali: Brilli, Andrea, Liuzzi, Giampaolo, Lucidi, Stefano
Natura: Preprint
Pubblicazione: 2021
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author Brilli, Andrea
Liuzzi, Giampaolo
Lucidi, Stefano
author_facet Brilli, Andrea
Liuzzi, Giampaolo
Lucidi, Stefano
contents In this paper we consider constrained optimization problems where both the objective and constraint functions are of the black-box type. Furthermore, we assume that the nonlinear inequality constraints are non-relaxable, i.e. their values and that of the objective function cannot be computed outside of the feasible region. This situation happens frequently in practice especially in the black-box setting where function values are typically computed by means of complex simulation programs which may fail to execute if the considered point is outside of the feasible region. For such problems, we propose a new derivative-free optimization method which is based on the use of a merit function that handles inequality constraints by means of a log-barrier approach and equality constraints by means of a quadratic penalty approach. We prove convergence of the proposed method to KKT stationary points of the problem under quite mild assumptions. Furthermore, we also carry out a preliminary numerical experience on standard test problems and comparison with a state-of-the-art solver which shows efficiency of the proposed method.
format Preprint
id arxiv_https___arxiv_org_abs_2108_05157
institution arXiv
publishDate 2021
record_format arxiv
spellingShingle An interior point method for nonlinear constrained derivative-free optimization
Brilli, Andrea
Liuzzi, Giampaolo
Lucidi, Stefano
Optimization and Control
65K05, 90C30, 90C56
In this paper we consider constrained optimization problems where both the objective and constraint functions are of the black-box type. Furthermore, we assume that the nonlinear inequality constraints are non-relaxable, i.e. their values and that of the objective function cannot be computed outside of the feasible region. This situation happens frequently in practice especially in the black-box setting where function values are typically computed by means of complex simulation programs which may fail to execute if the considered point is outside of the feasible region. For such problems, we propose a new derivative-free optimization method which is based on the use of a merit function that handles inequality constraints by means of a log-barrier approach and equality constraints by means of a quadratic penalty approach. We prove convergence of the proposed method to KKT stationary points of the problem under quite mild assumptions. Furthermore, we also carry out a preliminary numerical experience on standard test problems and comparison with a state-of-the-art solver which shows efficiency of the proposed method.
title An interior point method for nonlinear constrained derivative-free optimization
topic Optimization and Control
65K05, 90C30, 90C56
url https://arxiv.org/abs/2108.05157