Authors: Martin Peter Neuenhofen
We present an NLP solver for nonlinear optimization with quadratic penalty terms and logarithmic barrier terms. The method is suitable for large sparse problems. Each iteration has a polynomial time-complexity. The method has global convergence and local quadratic convergence, with a convergence radius that depends little on our method but rather on the geometry of the problem.
Comments: 16 Pages.
[v1] 2018-10-26 02:32:17
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