ISSN:
1573-2894
Keywords:
Successive Quadratic Programming
;
reduced Hessian methods
;
constrained optimization
;
quasi-Newton method
;
large-scale optimization
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
Notes:
Abstract The reduced Hessian SQP algorithm presented in Biegler et al. [SIAM J. Optimization, Vol. 5, no. 2, pp. 314–347, 1995.] is developed in this paper into a practical method for large-scale optimization. The novelty of the algorithm lies in the incorporation of a correction vector that approximates the cross term ZTWYpY. This improves the stability and robustness of the algorithm without increasing its computational cost. The paper studies how to implement the algorithm efficiently, and presents a set of tests illustrating its numerical performance. An analytic example, showing the benefits of the correction term, is also presented.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1008723031056
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