National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Application of quasi-Newton algorithm for solving a system of nonlinear equations
Esterlová, Alena ; Zatočilová, Jitka (referee) ; Tomášek, Petr (advisor)
This thesis focuses on solving macroeconomic models in the form of a system of nonlinear equations. These systems often exhibit a singular Jacobian matrix, which poses a~challenge in finding their solutions. This work introduces a suitable quasi-Newton method for such situations. Specifically, the Levenberg-Marquardt method and its modified two-step variant are chosen, proving to be effective tools for overcoming issues associated with singular Jacobian matrices. The selection of appropriate numerical methods used within the Levenberg-Marquardt method is also thoroughly examined.
A Modified Limited-Memory BNS Method for Unconstrained Minimization Derived from the Conjugate Directions Idea
Vlček, Jan ; Lukšan, Ladislav
A modification of the limited-memory variable metric BNS method for large scale unconstrained optimization of the differentiable function $f:{\cal R}^N\to\cal R$ is considered, which consists in corrections (based on the idea of conjugate directions) of difference vectors for better satisfaction of the previous quasi-Newton conditions. In comparison with [11], more previous iterations can be utilized here. For quadratic objective functions, the improvement of convergence is the best one in some sense, all stored corrected difference vectors are conjugate and the quasi-Newton conditions with these vectors are satisfied. The algorithm is globally convergent for convex sufficiently smooth functions and our numerical experiments indicate its efficiency.

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