We present new constraint qualification conditions for nonlinear semidefinite programming
that extend some of the constant rank-type conditions from nonlinear programming. As an …

A key problem in mathematical imaging, signal processing and computational statistics is
the minimization of non-convex objective functions that may be non-differentiable at the …

In this paper, we propose a primal-dual interior point trust-region method for solving
nonlinear semidefinite programming problems, in which the iterates converge to a point that …

Focusing on smooth constrained optimization problems, and inspired by the complementary
approximate Karush–Kuhn–Tucker (CAKKT) conditions, this work introduces the weighted …

Second-order necessary optimality conditions for nonlinear conic programming problems
that depend on a single Lagrange multiplier are usually built under nondegeneracy and …

We study properties of the central path underlying a nonlinear semidefinite optimization
problem, called NSDP for short. The latest radical work on this topic was contributed by …

In 2020, Yamakawa and Okuno proposed a stabilized sequential quadratic semidefinite
programming (SQSDP) method for solving, in particular, degenerate nonlinear semidefinite …

Nonlinear symmetric cone programming (NSCP) generalizes important optimization
problems such as nonlinear programming, nonlinear semi-definite programming and …

Sequential optimality conditions have played a major role in proving strong global
convergence properties of numerical algorithms for many classes of optimization problems …

We study the two-stage stochastic infinity norm optimization problem with recourse based on
a commutative algebra. First, we explore and develop the algebraic structure of the infinity …