Implementation of Infeasible Kernel-Based Interior-Point Methods for Linearly Constrained Convex Optimization

DOI

10.2991/eame-15.2015.178How to use a DOI?

Keywords

interior-point methods; kernel function; linearly constrained convex optimization; primal-dual methods; polynomial complexity

Abstract

In this paper, we present the implementation of infeasible kernel-based primal-dual interior-point methods for linearly constrained convex optimization. Numerical results are provided to demonstrate the efficiency of the algorithms.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - L. Wu
AU  - K. Li
AU  - X.D. Wang
AU  - L.H. Shao
AU  - A.N. Zhao
PY  - 2015/07
DA  - 2015/07
TI  - Implementation of Infeasible Kernel-Based Interior-Point Methods for Linearly Constrained Convex Optimization
BT  - Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering
PB  - Atlantis Press
SP  - 648
EP  - 651
SN  - 2352-5401
UR  - https://doi.org/10.2991/eame-15.2015.178
DO  - 10.2991/eame-15.2015.178
ID  - Wu2015/07
ER  -