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Autori principali: Liu, Ruyu, Pan, Shaohua
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2511.09940
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author Liu, Ruyu
Pan, Shaohua
author_facet Liu, Ruyu
Pan, Shaohua
contents This paper concerns a class of constrained optimization problems in which, the objective and constraint functions are both upper-$\mathcal{C}^2$. For such nonconvex and nonsmooth optimization problems, we develop an inexact moving balls approximation (MBA) method by a workable inexactness criterion for the solving of subproblems. By leveraging a global error bound for the strongly convex program associated with parametric optimization problems, we establish the full convergence of the iterate sequence under the partial bounded multiplier property (BMP) and the Kurdyka-Łojasiewicz (KL) property of the constructed potential function, and achieve the local convergence rate of the iterate and objective value sequences if the potential function satisfies the KL property of exponent $q\in[1/2,1)$. A verifiable condition is also provided to check whether the potential function satisfies the KL property of exponent $q\in[1/2,1)$ at the given critical point. To the best of our knowledge, this is the first implementable inexact MBA method with a full convergence certificate for the constrained nonconvex and nonsmooth optimization problem.
format Preprint
id arxiv_https___arxiv_org_abs_2511_09940
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Convergence analysis of inexact MBA method for constrained upper-$\mathcal{C}^2$ optimization problems
Liu, Ruyu
Pan, Shaohua
Optimization and Control
This paper concerns a class of constrained optimization problems in which, the objective and constraint functions are both upper-$\mathcal{C}^2$. For such nonconvex and nonsmooth optimization problems, we develop an inexact moving balls approximation (MBA) method by a workable inexactness criterion for the solving of subproblems. By leveraging a global error bound for the strongly convex program associated with parametric optimization problems, we establish the full convergence of the iterate sequence under the partial bounded multiplier property (BMP) and the Kurdyka-Łojasiewicz (KL) property of the constructed potential function, and achieve the local convergence rate of the iterate and objective value sequences if the potential function satisfies the KL property of exponent $q\in[1/2,1)$. A verifiable condition is also provided to check whether the potential function satisfies the KL property of exponent $q\in[1/2,1)$ at the given critical point. To the best of our knowledge, this is the first implementable inexact MBA method with a full convergence certificate for the constrained nonconvex and nonsmooth optimization problem.
title Convergence analysis of inexact MBA method for constrained upper-$\mathcal{C}^2$ optimization problems
topic Optimization and Control
url https://arxiv.org/abs/2511.09940