Complexity Analysis of Primal-Dual Interior-Point Methods for Linear Optimization Based on a New Parametric Kernel Function with a Trigonometric Barrier Term
| Autor: | X. Z. Cai, G. Q. Wang, M. El Ghami, Y. J. Yue |
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| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: | |
| Zdroj: | Abstract and Applied Analysis, Vol 2014 (2014) |
| Druh dokumentu: | article |
| ISSN: | 1085-3375 1687-0409 |
| DOI: | 10.1155/2014/710158 |
| Popis: | We introduce a new parametric kernel function, which is a combination of the classic kernel function and a trigonometric barrier term, and present various properties of this new kernel function. A class of large- and small-update primal-dual interior-point methods for linear optimization based on this parametric kernel function is proposed. By utilizing the feature of the parametric kernel function, we derive the iteration bounds for large-update methods, O(n2/3log(n/ε)), and small-update methods, O(nlog(n/ε)). These results match the currently best known iteration bounds for large- and small-update methods based on the trigonometric kernel functions. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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