The Development of the SQP Algorithm for Nonlinear Programming-Reference-Cited by-同舟云学术

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The Development of the SQP Algorithm for Nonlinear Programming

Published:1997 Issue: Volume: Page:1-19
ISSN:0940-6573
Container-title:Large-Scale Optimization with Applications
language:
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Author:

Sargent R. W. H.

Publisher

Springer New York

Link

http://link.springer.com/content/pdf/10.1007/978-1-4612-1960-6_1.pdf

Reference37 articles.

1. L. Armijo, Minimization of functions having Lipschitz continuous first partial derivatives, Pacific J. Math., 16 (1966), pp. 1–3.

2. L.T. Biegler, J. Nocedal and C. Schmid, A reduced Hessian method for large-scale constrained optimization, SIAM J. Optimization, 5 (2) (1995), pp. 314–347.

3. J.R. Bunch and B.N. Parlett, Direct methods for solving symmetric indefinite systems of linear equations, SIAM J. Numer. Anal., 8 (1971), pp. 639–655.

4. R.H. Byrd and J. Nocedal, An analysis of reduced-Hessian methods for constrained optimization, Math. Programming, 49 (1991), pp. 285–323.

5. R.M. Chamberlain, M.J.D. Powell, C. Lemarechal and H.C. Pedersen, The watchdog technique for forcing convergence in algorithms for constrained optimization, Math. Prog. Study, 17 (1982), pp. 1–17.

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