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Digitale Medien

Primal-Dual Path-Following Algorithms for Determinant Maximization Problems With Linear Matrix Inequalities (1999)

Toh, Kim-Chuan

Springer

Computational optimization and applications 14 (1999), S. 309-330

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ISSN: 1573-2894

Schlagwort(e): determinant optimization ; semidefinite programming ; predictor-corrector

Quelle: Springer Online Journal Archives 1860-2000

Thema: Informatik

Notizen: 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.

Materialart: Digitale Medien

URL: http://dx.doi.org/10.1023/A:1026400522929

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