Augmented self-concordant barriers and nonlinear optimization problems with finite complexity
Copyright policy )Augmented self-concordant barriers and nonlinear optimization problems with finite complexity
Augmented self-concordant barrier functions for convex cones, which are the sum of self-concordant barrier for the cone and a positive-semidifinite quadratic form, are studied. The complexity of finding the analytic center of these barrier functions is studied. It is shown that the complexity of a path-following method of barrier functions is independent of the particular data set for some special classes of quadratic forms and some convex cones. These problems form a class with finite polynomial complexity.
- Université Catholique de Louvain Belgium
- University of Geneva Switzerland
finite polynomial complexity, Nonlinear programming, Abstract computational complexity for mathematical programming problems, barrier function, nonlinear optimization, central path
finite polynomial complexity, Nonlinear programming, Abstract computational complexity for mathematical programming problems, barrier function, nonlinear optimization, central path
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