Algorithms for unsymmetric cone optimization and an implementation for problems with the exponential cone
Abstract/Contents
- Abstract
- Symmetric cone optimization subsumes linear optimization, second-order cone optimization, and semidefinite optimization. It is of interest to extend the algorithmic developments of symmetric cone optimization into the realm of unsymmetric cones. We analyze the theoretical properties of some algorithms for unsymmetric cone problems. We show that they achieve excellent worst-case iteration bounds while not necessarily being practical to implement. Using lessons from this analysis and inspired by the Mehrotra predictor-corrector algorithm, we extend the homogeneous implementation ECOS to handle problems modeled with Cartesian products of the positive orthant, second-order cones, and the exponential cone, and we empirically validate its efficiency.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2015 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Akle Serrano, Santiago |
|---|---|
| Associated with | Stanford University, Institute for Computational and Mathematical Engineering. |
| Primary advisor | Saunders, Michael |
| Primary advisor | Ye, Yinyu |
| Thesis advisor | Saunders, Michael |
| Thesis advisor | Ye, Yinyu |
| Thesis advisor | Gerritsen, Margot (Margot G.) |
| Advisor | Gerritsen, Margot (Margot G.) |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Santiago Akle Serrano. |
|---|---|
| Note | Submitted to the Institute for Computational and Mathematical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2015. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2015 by Santiago Akle Serrano
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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