Bound constrained quadratic programming via piecewise quadratic functions

被引：0
|
作者：
Kaj Madsen
Hans Bruun Nielsen
Mustafa Ç. Pınar
机构：
[1] Institute of Mathematical Modelling,
[2] Technical University of Denmark,undefined
[3] 2800 Lyngby,undefined
[4] Denmark,undefined
[5] e-mail: km@imm.dtu.dk,undefined
[6] hbn@imm.dtu.dk,undefined
[7] Department of Industrial Engineering,undefined
[8] Bilkent University,undefined
[9] 06533 Bilkent,undefined
[10] Ankara,undefined
[11] Turkey,undefined
[12] e-mail: mustafap@Bilkent.EDU.TR,undefined
来源：
Mathematical Programming | 1999年 / 85卷
关键词：
Key words: bound constrained quadratic programming – Huber’s M–estimator – condition estimation – Newton iteration – factorization update;
D O I：
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学科分类号：
摘要：
, the smallest eigenvalue of a symmetric, positive definite matrix, and is solved by Newton iteration with line search. The paper describes the algorithm and its implementation including estimation of λ1, how to get a good starting point for the iteration, and up- and downdating of Cholesky factorization. Results of extensive testing and comparison with other methods for constrained QP are given.
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页码：135 / 156
页数：21
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