Electronic Resource
Springer
Journal of optimization theory and applications
60 (1989), S. 453-473
ISSN:
1573-2878
Keywords:
Sequential quadratic programming
;
large-scale programming
;
nonlinear programming
;
incomplete Cholesky factorization
;
quadratic programming
;
dual methods
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Abstract Described here is the structure and theory for a sequential quadratic programming algorithm for solving sparse nonlinear optimization problems. Also provided are the details of a computer implementation of the algorithm along with test results. The algorithm maintains a sparse approximation to the Cholesky factor of the Hessian of the Lagrangian. The solution to the quadratic program generated at each step is obtained by solving a dual quadratic program using a projected conjugate gradient algorithm. An updating procedure is employed that does not destroy sparsity.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00940348
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