New approach for Secant Update generalized version of PSB

Working with Quasi-Newton methods in optimization leads to one important challenge, being to find an estimate of the Hessian matrix as close as possible to the real matrix. While multisecant methods are regularly used to solve root finding problems, they have been little explored in optimization because the symmetry property of the Hessian matrix estimation is generally not compatible with the multisecant property. In this paper, we propose a solution to apply multisecant methods to optimization problems. Starting from the Powell-Symmetric-Broyden (PSB) update formula and adding pieces of information from the previous steps of the optimization path, we want to develop a new update formula for the estimate of the Hessian. A multisecant version of PSB is, however, generally mathematically impossible to build. For that reason, we provide a formula that satisfies the symmetry and is as close as possible to satisfy the multisecant condition and vice versa for a second formula. Subsequently, we add enforcement of the last secant equation to the symmetric formula and present a comparison between the different methods.

[1]  Serge Gratton,et al.  Quasi-Newton updates with weighted secant equations , 2015, Optim. Methods Softw..

[2]  Warren Hare,et al.  Best practices for comparing optimization algorithms , 2017, Optimization and Engineering.

[3]  Jorge J. Moré,et al.  Digital Object Identifier (DOI) 10.1007/s101070100263 , 2001 .

[4]  Joris Degroote,et al.  Secant Update generalized version of PSB: a new approach , 2021, Computational Optimization and Applications.

[5]  K. Bathe,et al.  Performance of a new partitioned procedure versus a monolithic procedure in fluid-structure interaction , 2009 .

[6]  Joris Degroote,et al.  Secant update version of quasi-Newton PSB with weighted multisecant equations , 2020, Comput. Optim. Appl..

[7]  Joris Degroote,et al.  Quasi-Newton methods for the acceleration of multi-physics codes , 2017 .

[8]  J. J. Moré,et al.  Quasi-Newton Methods, Motivation and Theory , 1974 .

[9]  Nicholas I. M. Gould,et al.  CUTEst: a Constrained and Unconstrained Testing Environment with safe threads for mathematical optimization , 2013, Computational Optimization and Applications.

[10]  José Mario Martínez,et al.  A Limited-Memory Multipoint Symmetric Secant Method for Bound Constrained Optimization , 2002, Ann. Oper. Res..

[11]  R. Schnabel Quasi-Newton Methods Using Multiple Secant Equations. , 1983 .

[12]  R. Plessix A review of the adjoint-state method for computing the gradient of a functional with geophysical applications , 2006 .

[13]  M. J. D. Powell,et al.  Beyond symmetric Broyden for updating quadratic models in minimization without derivatives , 2013, Math. Program..

[14]  H. J. Martínez,et al.  Least Change Secant Update Methods for Nonlinear Complementarity Problem , 2015 .

[15]  Robby Haelterman,et al.  Improving the performance of the partitioned QN-ILS procedure for fluid-structure interaction problems , 2016 .