Primal-dual Interior-point Algorithms for Second-order Cone Optimization Based on a New Parametric Kernel Function

Author:

Bai Yan Qin,Wang Guo Qiang

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,General Mathematics

Reference16 articles.

1. Adler, I., Alizadeh, F.: Primal-dual interior point algorithms for convex quadratically constrained and semidefinite optimization promblems, Technical report RRR-111-95, Rutgers Center for Operations Research, New Brunswick, NJ, 1995

2. Peng, J., Roos, C., Terlaky, t.: Self-Regularity. A New Paradigm for Primal–Dual Interior–Point Algorithms, Princeton University Press, Princeton, NJ, 2002

3. Wang, G. Q., Bai, Y. Q., Roos, C.: Primal-dual interior-point algorithms for semidefinite optimization based on a simple kernel function. Journal of Mathematical Modelling and Algorithms, 4, 409–433 (2005)

4. Huang, X. X., Teo, K. L, Yang, X. Q.: Approximate augmented Lagrangian functions and nonlinear semidefinite programs. Acta Mathematica Sinica, English Series, 22(5), 1283–1296 (2006)

5. Lobo, M. S., Vandenberghe, L., Boyd, S., Lebret, H.: Applications of the second-order cone programming. Linear Algebra and Applications, 284, 193–228 (1998)

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