Nonlinear Derivative-free Constrained Optimization with a Penalty-Interior Point Method and Direct Search

Fuente: arXiv
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Autores principales: Brilli, Andrea, Custódio, Ana L., Liuzzi, Giampaolo, Silva, Everton J.
Formato: Preprint
Publicado: 2024
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author Brilli, Andrea
Custódio, Ana L.
Liuzzi, Giampaolo
Silva, Everton J.
author_facet Brilli, Andrea
Custódio, Ana L.
Liuzzi, Giampaolo
Silva, Everton J.
contents In this work, the joint use of a mixed penalty-interior point method and direct search is proposed, to address {nonlinear} constrained derivative-free optimization problems. A merit function is considered, wherein the set of nonlinear inequality constraints is divided into two groups: one treated with a logarithmic barrier approach, and another, along with the equality constraints, addressed using a penalization term. This strategy is adapted and incorporated into a direct search method, enabling the effective handling of general nonlinear constraints. Convergence to KKT-stationary points is established under continuous differentiability assumptions, without requiring any kind of convexity. Computational experiments on analytical problems and an engineering application demonstrate the robustness, efficiency, and overall effectiveness of the proposed method, when compared with state-of-the-art solvers.
format Preprint
id arxiv_https___arxiv_org_abs_2407_21634
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Nonlinear Derivative-free Constrained Optimization with a Penalty-Interior Point Method and Direct Search
Brilli, Andrea
Custódio, Ana L.
Liuzzi, Giampaolo
Silva, Everton J.
Optimization and Control
65K05, 90C30, 90C56
In this work, the joint use of a mixed penalty-interior point method and direct search is proposed, to address {nonlinear} constrained derivative-free optimization problems. A merit function is considered, wherein the set of nonlinear inequality constraints is divided into two groups: one treated with a logarithmic barrier approach, and another, along with the equality constraints, addressed using a penalization term. This strategy is adapted and incorporated into a direct search method, enabling the effective handling of general nonlinear constraints. Convergence to KKT-stationary points is established under continuous differentiability assumptions, without requiring any kind of convexity. Computational experiments on analytical problems and an engineering application demonstrate the robustness, efficiency, and overall effectiveness of the proposed method, when compared with state-of-the-art solvers.
title Nonlinear Derivative-free Constrained Optimization with a Penalty-Interior Point Method and Direct Search
topic Optimization and Control
65K05, 90C30, 90C56
url https://arxiv.org/abs/2407.21634