Generalized conjugate gradient algorithm for solving a class of quadratic programming problems
Technical Report
·
OSTI ID:6682383
Matrix splitting techniques and a conjugate gradient algorithm are applied to the problem of minimizing a convex quadratic form subject to upper and lower bounds on the variables. This method exploits sparsity structure in the matrix of the quadratic form. Choices of the splitting operator are discussed and convergence results are established. Results are presented of numerical experiments showing the effectiveness of the algorithm on free boundary problems for elliptic partial differential equations; comparisons with other algorithms are given. 8 figures, 2 tables.
- Research Organization:
- Stanford Univ., CA (USA). Dept. of Computer Science
- OSTI ID:
- 6682383
- Report Number(s):
- SU-326-P30-57
- Country of Publication:
- United States
- Language:
- English
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