A stabilized sequential quadratic semidefinite programming method for degenerate nonlinear semidefinite programs
A stabilized sequential quadratic semidefinite programming method for degenerate nonlinear semidefinite programs is a scholarly work, published in 2022 in ''Computational Optimization and Applications''. The main subjects of the publication include Semidefinite embedding, mathematical optimization, mathematics, interior point method, second-order cone programming, Trust region, definite matrix, large margin nearest neighbor, applied mathematics, convergence, Sequential quadratic programming, stationary point, quadratic equation, Minimax, Lagrange multiplier, nonlinear programming, semidefinite programming, iterative numerical method, degenerate energy level, quadratically constrained quadratic program, nonlinear system, compressed sensing, and quadratic programming. The authors propose a new sequential quadratic semidefinite programming\n(SQSDP) method for solving degenerate nonlinear semidefinite programs (NSDPs),\nin which authors produce iteration points by solving a sequence of stabilized\nquadratic semidefinite programming (QSDP) subproblems, which authors derive from the\nminimax problem associated with the NSDP.