Solving structured nonlinear least-squares and nonlinear feasibility problems with expensive functions

Markus Kaiser, Kathrin Klamroth, Alexander Thekale, Philippe Toint

Résultats de recherche: Livre/Rapport/RevueAutre rapport

Résumé

We present an algorithm for nonlinear least-squares and nonlinear feasibility problems, i.e. for systems of nonlinear equations and nonlinear inequalities, which depend on the outcome of expensive functions for which derivatives are assumed to be unavailable. Our algorithm combines derivative-free techniques with filter trust-region methods to keep the number of expensive function evaluations low and to obtain a robust method. Under adequate assumptions, we show global convergence to a feasible point. Numerical results indicate a significant reduction in function evaluations compared to other derivative based and derivative-free solvers for nonlinear feasibility problems.
langue originaleAnglais
Lieu de publicationNamur
EditeurFUNDP. Namur center for complex systems
Volume10(7)
Etat de la publicationPublié - 2010

Série de publications

NomNAXYS Technical Report
EditeurDepartment of Mathematics, University of Namur
Volume07-2010

    Empreinte digitale

Contient cette citation

Kaiser, M., Klamroth, K., Thekale, A., & Toint, P. (2010). Solving structured nonlinear least-squares and nonlinear feasibility problems with expensive functions. (NAXYS Technical Report; Vol 07-2010). FUNDP. Namur center for complex systems.