A convergence proof for an affine-scaling algorithm for convex quadratic programming without nondegeneracy assumptions |
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Authors: | Jie Sun |
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Institution: | (1) Department of Industrial Engineering and Management Sciences, Northwestern University, 2145 Sheridan Road, 60208-3119 Evanston, IL, USA |
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Abstract: | This paper presents a theoretical result on convergence of a primal affine-scaling method for convex quadratic programs. It is shown that, as long as the stepsize is less than a threshold value which depends on the input data only, Ye and Tse's interior ellipsoid algorithm for convex quadratic programming is globally convergent without nondegeneracy assumptions. In addition, its local convergence rate is at least linear and the dual iterates have an ergodically convergent property.Research supported in part by the NSF under grant DDM-8721709. |
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Keywords: | Quadratic programming interior point methods affine-scaling methods |
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