A polynomial-time interior-point algorithm for convex quadratic semidefinite optimization
RAIRO - Operations Research - Recherche Opérationnelle, Tome 44 (2010) no. 3, pp. 251-265.

In this paper we propose a primal-dual interior-point algorithm for convex quadratic semidefinite optimization problem. The search direction of algorithm is defined in terms of a matrix function and the iteration is generated by full-Newton step. Furthermore, we derive the iteration bound for the algorithm with small-update method, namely, O(n log n ε), which is best-known bound so far.

DOI : 10.1051/ro/2010016
Classification : 90C05, 90C51
Mots-clés : convex quadratic semidefinite optimization, interior-point algorithm, small-update method, iteration bound, polynomial-time 
@article{RO_2010__44_3_251_0,
     author = {Bai, Y. Q. and Wang, F. Y. and Luo, X. W.},
     title = {A polynomial-time interior-point algorithm for convex quadratic semidefinite optimization},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
     pages = {251--265},
     publisher = {EDP-Sciences},
     volume = {44},
     number = {3},
     year = {2010},
     doi = {10.1051/ro/2010016},
     mrnumber = {2762796},
     zbl = {1203.90178},
     language = {en},
     url = {http://archive.numdam.org/articles/10.1051/ro/2010016/}
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Bai, Y. Q.; Wang, F. Y.; Luo, X. W. A polynomial-time interior-point algorithm for convex quadratic semidefinite optimization. RAIRO - Operations Research - Recherche Opérationnelle, Tome 44 (2010) no. 3, pp. 251-265. doi : 10.1051/ro/2010016. http://archive.numdam.org/articles/10.1051/ro/2010016/

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