A prediction-correction inexact alternating direction method for convex nonlinear second-order cone programming with linear constraints

摘要

The convex nonlinear second-order cone programming with linear constraints is equivalent to a separate structure convex programming. A prediction-correction inexact alternating direction method is proposed for the separate structure convex programming. In the proposed method, the convex objective function is not required to be Lipschitz continuous and only needs satisfy an inequality. The global convergence result is given. Numerical results demonstrate that our method is efficient for some random second-order cone programming problems in lower accuracy. In addition, our method can be extended to the convex nonlinear circular cone programming with linear constraints. We also give the simulation results of the three-fingered grasping force optimization problems.