Application of the Infinitely Many Times Repeated BNS Update and Conjugate Directions to Limited-Memory Optimization Methods

0504548 - ÚI 2020 RIV CZ eng C - Conference Paper (international conference)
Vlček, Jan - Lukšan, Ladislav
Application of the Infinitely Many Times Repeated BNS Update and Conjugate Directions to Limited-Memory Optimization Methods.
Programs and Algorithms of Numerical Mathematics 19. Prague: Institute of Mathematics of the Czech Academy of Sciences, 2019 - (Chleboun, J.; Kůs, P.; Přikryl, P.; Rozložník, M.; Segeth, K.; Šístek, J.; Vejchodský, T.), s. 177-185. ISBN 978-80-85823-69-1.
[Programs and Algorithms of Numerical Mathematics /19./. Hejnice (CZ), 24.06.2018-29.06.2018]
Institutional support: RVO:67985807
Keywords : unconstrained minimization * limited-memory variable metric methods * the repeated Byrd-Nocedal-Schnabel update * the Lyapunov matrix equation * the conjugate directions * global convergence * numerical results
OECD category: Applied mathematics

To improve the performance of the L-BFGS method for large scale unconstrained optimization, repeating of some BFGS updates was proposed. Since this can be time consuming, the extra updates need to be selected carefully. We show that groups of these updates can be repeated infinitely many times under some conditions, without a noticeable increase of the computational time. The limit update is a block BFGS update. It can be obtained by solving of some Lyapunov matrix equation whose order can be decreased by application of vector corrections for conjugacy. Global convergence of the proposed algorithm is established for convex and sufficiently smooth functions. Numerical results indicate the efficiency of the new method.
Permanent Link: http://hdl.handle.net/11104/0296152