Abstract
In this paper, we propose an algorithm based on Fletcher’s Sl1QP method and the trust region technique for solving Nonlinear Second-Order Cone Programming (NSOCP) problems. The Sl1QP method was originally developed for nonlinear optimization problems with inequality constraints. It converts a constrained optimization problem into an unconstrained problem by using the l1 exact penalty function, and then finds an optimum by solving approximate quadratic programming subproblems successively. In order to apply the Sl1QP method to the NSOCP problem, we introduce an exact penalty function with respect to second-order cone constraints and reformulate the NSOCP problem as an unconstrained optimization problem. However, since each subproblem generated by the Sl1QP method is not differentiable, we reformulate it as a second-order cone programming problem whose objective function is quadratic and constraint functions are affine. We analyze the convergence property of the proposed algorithm, and show that the generated sequence converge to a stationary point of the NSOCP problem under mild assumptions. We also confirm the efficiency of the algorithm by means of numerical experiments.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
