In this paper, a new inexact smoothing method is presented for solving the symmetric conic linear programming (SCLP) in materials. Based on a regularized version of Chen-Harker-Kanzow-Smale smoothing function, our algorithm reformulates the SCLP as an equivalent nonlinear system of equations. At each iteration, Newtons method is adopted to solve the system approximately. Under suitable assumptions, the algorithm is proved to possess global convergence and local superlinear convergence.
Strong Duality in Conic Linear Programming: Facial Reduction and Extended Duals
