Projected Adaptive Cubic Regularization Algorithm with Derivative-Free Filter Technique for Box Constrained Optimization

An adaptive projected affine scaling algorithm of cubic regularization method using a filter technique for solving box constrained optimization without derivatives is put forward in the passage. The affine scaling interior-point cubic model is based on the quadratic probabilistic interpolation appro...

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Autores principales:	Lingyun He, Peng Wang, Detong Zhu
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/7a93f4f648474efcab4c0ae166accbf1
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id	oai:doaj.org-article:7a93f4f648474efcab4c0ae166accbf1
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spelling	oai:doaj.org-article:7a93f4f648474efcab4c0ae166accbf12021-11-08T02:36:19ZProjected Adaptive Cubic Regularization Algorithm with Derivative-Free Filter Technique for Box Constrained Optimization1607-887X10.1155/2021/1496048https://doaj.org/article/7a93f4f648474efcab4c0ae166accbf12021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/1496048https://doaj.org/toc/1607-887XAn adaptive projected affine scaling algorithm of cubic regularization method using a filter technique for solving box constrained optimization without derivatives is put forward in the passage. The affine scaling interior-point cubic model is based on the quadratic probabilistic interpolation approach on the objective function. The new iterations are obtained by the solutions of the projected adaptive cubic regularization algorithm with filter technique. We prove the convergence of the proposed algorithm under some assumptions. Finally, experiments results showed that the presented algorithm is effective in detail.Lingyun HePeng WangDetong ZhuHindawi LimitedarticleMathematicsQA1-939ENDiscrete Dynamics in Nature and Society, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Mathematics QA1-939
spellingShingle	Mathematics QA1-939 Lingyun He Peng Wang Detong Zhu Projected Adaptive Cubic Regularization Algorithm with Derivative-Free Filter Technique for Box Constrained Optimization
description	An adaptive projected affine scaling algorithm of cubic regularization method using a filter technique for solving box constrained optimization without derivatives is put forward in the passage. The affine scaling interior-point cubic model is based on the quadratic probabilistic interpolation approach on the objective function. The new iterations are obtained by the solutions of the projected adaptive cubic regularization algorithm with filter technique. We prove the convergence of the proposed algorithm under some assumptions. Finally, experiments results showed that the presented algorithm is effective in detail.
format	article
author	Lingyun He Peng Wang Detong Zhu
author_facet	Lingyun He Peng Wang Detong Zhu
author_sort	Lingyun He
title	Projected Adaptive Cubic Regularization Algorithm with Derivative-Free Filter Technique for Box Constrained Optimization
title_short	Projected Adaptive Cubic Regularization Algorithm with Derivative-Free Filter Technique for Box Constrained Optimization
title_full	Projected Adaptive Cubic Regularization Algorithm with Derivative-Free Filter Technique for Box Constrained Optimization
title_fullStr	Projected Adaptive Cubic Regularization Algorithm with Derivative-Free Filter Technique for Box Constrained Optimization
title_full_unstemmed	Projected Adaptive Cubic Regularization Algorithm with Derivative-Free Filter Technique for Box Constrained Optimization
title_sort	projected adaptive cubic regularization algorithm with derivative-free filter technique for box constrained optimization
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/7a93f4f648474efcab4c0ae166accbf1
work_keys_str_mv	AT lingyunhe projectedadaptivecubicregularizationalgorithmwithderivativefreefiltertechniqueforboxconstrainedoptimization AT pengwang projectedadaptivecubicregularizationalgorithmwithderivativefreefiltertechniqueforboxconstrainedoptimization AT detongzhu projectedadaptivecubicregularizationalgorithmwithderivativefreefiltertechniqueforboxconstrainedoptimization
_version_	1718443107629924352

Projected Adaptive Cubic Regularization Algorithm with Derivative-Free Filter Technique for Box Constrained Optimization

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