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Yu Xia (yuxiacas.mcmaster.ca) Abstract: The secondorder 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 Qquadratically 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. Keywords: Secondorder cone, complementarity, semismooth, warm start, Newton's method Category 1: Linear, Cone and Semidefinite Programming (SecondOrder Cone Programming ) Category 2: Convex and Nonsmooth Optimization (Nonsmooth Optimization ) Category 3: Complementarity and Variational Inequalities Citation: AdvOlReport#2004/17 McMaster University, Advanced Optimization Laboratory Hamilton, Ontario, Canada October 2004 Download: [Postscript][PDF] Entry Submitted: 10/16/2004 Modify/Update this entry  
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