A class of nonconvex semidefinite programming in which every KKT point is globally optimal

Akatsuki Nishioka; Yoshihiro Kanno

A class of nonconvex semidefinite programming in which every KKT point is globally optimal

Optimization and Control 2025-06-23 v1

Authors: Akatsuki Nishioka , Yoshihiro Kanno

Abstract

We consider a special class of nonconvex semidefinite programming problems and show that every point satisfying the Karush--Kuhn--Tucker (KKT) conditions is globally optimal despite nonconvexity. This property is related to pseudoconvex optimization. This class of problems is motivated by an eigenfrequency topology optimization problem in structural engineering, but is presented in a more general form.

Keywords

nonconvex semidefinite programming KKT conditions global optimality pseudoconvex optimization eigenfrequency topology optimization

Cite

@article{arxiv.2506.16739,
  title  = {A class of nonconvex semidefinite programming in which every KKT point is globally optimal},
  author = {Akatsuki Nishioka and Yoshihiro Kanno},
  journal= {arXiv preprint arXiv:2506.16739},
  year   = {2025}
}

Comments

10 pages, 1 figure

Related papers

View all related →