Relationship between the BFGS and conjugate gradient algorithms
Based upon analysis and numerical experience, the BFGS algorithm is currently considered to be one of the most effective algorithms for finding a minimum of an unconstrained function, f(x), x an element of IR/sup n/. However, when computer storage is at a premium, the usual alternative is to use a conjugate gradient (CG) method. This paper shows that the two algorithms are related to one another in a particularly close way. Based upon these observations, a new family of algorithms is proposed.
- Research Organization:
- Argonne National Lab., IL (USA)
- OSTI ID:
- 7220579
- Report Number(s):
- ANL-AMD-TM-282(Rev.)
- Country of Publication:
- United States
- Language:
- English
Similar Records
Relationship between the BFGS and conjugate gradient algorithms and its implications for new algorithms
Generalized conjugate gradient squared
Preconditioned conjugate gradient algorithms and software for solving large sparse linear systems
Journal Article
·
Mon Oct 01 00:00:00 EDT 1979
· SIAM J. Numer. Anal.; (United States)
·
OSTI ID:5401317
Generalized conjugate gradient squared
Conference
·
Fri Dec 30 23:00:00 EST 1994
·
OSTI ID:219554
Preconditioned conjugate gradient algorithms and software for solving large sparse linear systems
Conference
·
Sat Feb 28 23:00:00 EST 1987
·
OSTI ID:5383477