1
, 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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Received May 1, 1997 / Revised version received March 17, 1998 Published online November 24, 1998
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Madsen, K., Nielsen, H. & Pınar, M. Bound constrained quadratic programming via piecewise quadratic functions. Math. Program. 85, 135–156 (1999). https://doi.org/10.1007/s101070050049
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DOI: https://doi.org/10.1007/s101070050049