Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/103971
Title: Primal-dual path-following algorithms for determinant maximization problems with linear matrix inequalities
Authors: Toh, K.-C. 
Issue Date: 1999
Source: Toh, K.-C. (1999). Primal-dual path-following algorithms for determinant maximization problems with linear matrix inequalities. Computational Optimization and Applications 14 (3) : 309-330. ScholarBank@NUS Repository.
Abstract: Primal-dual path-following algorithms are considered for determinant maximization problem (maxdet-problem). These algorithms apply Newton's method to a primal-dual central path equation similar to that in semidefinite programming (SDP) to obtain a Newton system which is then symmetrized to avoid nonsymmetric search direction. Computational aspects of the algorithms are discussed, including Mehrotra-type predictor-corrector variants. Focusing on three different symmetrizations, which leads to what are known as the AHO, H..K..M and NT directions in SDP, numerical results for various classes of maxdet-problem are given. The computational results show that the proposed algorithms are efficient, robust and accurate.
Source Title: Computational Optimization and Applications
URI: http://scholarbank.nus.edu.sg/handle/10635/103971
ISSN: 09266003
Appears in Collections:Staff Publications

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