Leírás
CCOR Optimalizálási szeminárium
Abstract:
Linear Complementarity Problems (LCP) is an important class of problems closely related to many optimization problems. Thus, efficient algorithms for solving LCP are of the interest for theoretical and practical purposes.
The Feasible Interior-Point Methods (IPM) based on the class of eligible kernel functions will be presented. This class is fairly general and includes the classical logarithmic function, the prototype self-regular function, and non-self-regular kernel functions as special cases. We will show that the method globally converges and iteration bounds to obtain epsilon-approximate solution matches best known iteration bounds for these types of methods. In particular, one of the main achievements of the kernel-based IPMs is the improved complexity of long-step methods. We will briefly outline the complexity analysis of IPMs based on several particular kernel functions.
We will conclude the talk by briefly discussing generalization of these methods to the class of LCPs over symmetric cones if time permits.
For Zoom access please contact E.-Nagy Marianna (marianna.eisenberg-nagy[at]uni-corvinus.hu).