Globally and superlinearly convergent trust-region algorithm for convex SC1-minimization problems and its application to stochastic programs
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Management Science and Operations Research,Control and Optimization
Link
http://link.springer.com/content/pdf/10.1007/BF02189800.pdf
Reference27 articles.
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3. Qi, L., andWomersley, R.,An SQPAlgorithm for Extended Linear-Quadratic Problems in Stochastic Programming, Annals of Operations Research, Vol. 56, pp. 251–285, 1995.
4. Qi, L.,Superlinearly Convergent Approximate Newton Methods for LC 1 Optimiziation Problems, Mathematical Programming, Vol. 64, pp. 277–294, 1994.
5. Garcia Palomares, U. M., andMangasarian, O. L.,Superlinearly Convergent Quasi-Newton Algorithm for Nonlinearly Constrained Optimization Problems, Mathematical Programming, Vol. 11, pp. 1–13, 1976.
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3. A globally and superlinearly convergent trust region method for LC 1 optimization problems;Applied Mathematics-A Journal of Chinese Universities;2001-03
4. On the Constant Positive Linear Dependence Condition and Its Application to SQP Methods;SIAM Journal on Optimization;2000-01
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