On the Superlinear Convergence of Interior-Point Algorithms for a General Class of Problems

  title={On the Superlinear Convergence of Interior-Point Algorithms for a General Class of Problems},
  author={Yin Zhang and Richard A. Tapia and Florian A. Potra},
  journal={SIAM J. Optim.},
In this paper, the authors extend the Q-superlinear convergence theory recently developed by Zhang, Tapia, and Dennis for a class of interior-point linear programming algorithms to similar interior-point algorithms for quadratic programming and for linear complementarily problems. This unified approach consists of viewing all these algorithms as a damped Newton method applied to perturbations of a general problem. A set of sufficient conditions for these algorithms to achieve Q-superlinear… 
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Interior-point algorithms for global optimization
  • Y. Ye
  • Computer Science
  • 1990
We describe recent developments in interior-point algorithms for global optimization. We will focus on the algorithmic research for nonconvex quadratic programming, linear complementarity problem,