An Algorithm for Perturbed Second-order Cone Programs

The second-order cone programming problem is reformulated into several new systems of nonlinear equations. Assume the perturbation of the data is in a certain neighborhood of zero. Then starting from a solution to the old problem, the semismooth Newton’s iterates converge Q-quadratically to a solution of the perturbed problem. The algorithm is globalized. Numerical examples show that the algorithm is good for “warm starting” — for some instances, the solution of a perturbed problem is hit in two iterations.

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AdvOl-Report#2004/17 McMaster University, Advanced Optimization Laboratory Hamilton, Ontario, Canada October 2004

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