王承竞 副教授
  • 学历:博士研究生毕业
  • 学位:理学博士学位
  • 办公地点:西南交通大学数学学院
  • 毕业院校:新加坡国立大学
  • 所在单位:数学学院
论文成果
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  • 发表刊物:Set-Valued and Variational Analysis
  • 摘要:This paper investigates a recently introduced notion of strong variational sufficiency in optimization problems whose importance has been highly recognized in optimization theory, numerical methods, and applications. We address a general class of composite optimization problems and establish complete characterizations of strong variational sufficiency for their local minimizers in terms of a generalized version of the strong second-order sufficient condition (SSOSC) and the positive-definiteness of an appropriate generalized Hessian of the augmented Lagrangian calculated at the point in question. The generalized SSOSC is expressed via a novel second-order variational function, which reflects specific features of nonconvex composite models. The imposed assumptions describe the spectrum of composite optimization problems covered by our approach while being constructively implemented for nonpolyhedral problems that involve the nuclear norm function and the indicator function of the positive-semidefinite cone without any constraint qualifications.
  • 合写作者:Chengjing Wang
  • 第一作者:Boris Mordukhovich
  • 通讯作者:Peipei Tang
  • 卷号:34
  • 页面范围:1-25
  • 是否译文:
  • 发表时间:2026-04-01
  • 收录刊物:SCI
  • 附件: Published_version_Characterizations of Strong Variational Sufficiency in General.pdf

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