TY - JOUR
T1 - Secant Update generalized version of PSB
T2 - a new approach
AU - Boutet, Nicolas
AU - Haelterman, Rob
AU - Degroote, Joris
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.
PY - 2021/4
Y1 - 2021/4
N2 - In optimization, one of the main challenges of the widely used family of Quasi-Newton methods is to find an estimate of the Hessian matrix as close as possible to the real matrix. In this paper, we develop a new update formula for the estimate of the Hessian starting from the Powell-Symetric-Broyden (PSB) formula and adding pieces of information from the previous steps of the optimization path. This lead to a multisecant version of PSB, which we call generalised PSB (gPSB), but which does not exist in general as was proven before. We provide a novel interpretation of this non-existence. In addition, we provide a formula that satisfies the multisecant condition and is as close to symmetric as possible and vice versa for a second formula. Subsequently, we add enforcement of the last secant equation and present a comparison between the different methods.
AB - In optimization, one of the main challenges of the widely used family of Quasi-Newton methods is to find an estimate of the Hessian matrix as close as possible to the real matrix. In this paper, we develop a new update formula for the estimate of the Hessian starting from the Powell-Symetric-Broyden (PSB) formula and adding pieces of information from the previous steps of the optimization path. This lead to a multisecant version of PSB, which we call generalised PSB (gPSB), but which does not exist in general as was proven before. We provide a novel interpretation of this non-existence. In addition, we provide a formula that satisfies the multisecant condition and is as close to symmetric as possible and vice versa for a second formula. Subsequently, we add enforcement of the last secant equation and present a comparison between the different methods.
KW - Multisecant equations
KW - Non-linear optimization
KW - Quasi-Newton formulae
KW - Symmetric gradient
UR - http://www.scopus.com/inward/record.url?scp=85099401620&partnerID=8YFLogxK
U2 - 10.1007/s10589-020-00256-1
DO - 10.1007/s10589-020-00256-1
M3 - Article
AN - SCOPUS:85099401620
SN - 0926-6003
VL - 78
SP - 953
EP - 982
JO - Computational Optimization and Applications
JF - Computational Optimization and Applications
IS - 3
ER -