Abstract
A class of large- and small- update primal-dual interior-point point algorithms for linear optimization is presented. The calculation of the search direction is based on new kernel function. The kernel function is an extension of the self-regular function; however it is not self-regular due to the fact that its growth term increases linearly. We develop new analysis tools that are used in complexity analysis of the algorithms and obtain favorable polynomial complexity bounds.
| Original language | American English |
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| State | Published - Nov 13 2005 |
| Event | Institute for Operations Research and the Management Sciences Annual Conference (INFORMS) - Duration: Oct 1 2017 → … |
Conference
| Conference | Institute for Operations Research and the Management Sciences Annual Conference (INFORMS) |
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| Period | 10/1/17 → … |
Disciplines
- Mathematics
- Physical Sciences and Mathematics
Keywords
- Algorithms
- Interior-Point
- Large
- Linear Optimization
- Primal-Dual
- Small