@article{98ab0b9dc77941f0b53dd07cb34758b4,
title = "An active-set trust-region method for derivative-free nonlinear bound-constrained optimization",
abstract = "We consider an implementation of a recursive model-based active-set trust-region method for solving bound-constrained nonlinear non-convex optimization problems without derivatives using the technique of self-correcting geometry proposed in K. Scheinberg and Ph.L. Toint [Self-correcting geometry in model-based algorithms for derivative-free unconstrained optimization. SIAM Journal on Optimization, (to appear), 2010]. Considering an active-set method in bound-constrained model-based optimization creates the opportunity of saving a substantial amount of function evaluations. It allows US to maintain much smaller interpolation sets while proceeding optimization in lower-dimensional subspaces. The resulting algorithm is shown to be numerically competitive. {\textcopyright} 2011 Taylor & Francis.",
keywords = " trust region, active-set methods, bound constraints, numerical experiments, nonlinear optimization, derivative-free optimization",
author = "Serge Gratton and Philippe Toint and Anke Tr{\"o}ltzsch",
note = "Publication code : FP SB092/2010/01 ; SB04977/2010/01",
year = "2011",
month = aug,
day = "1",
doi = "10.1080/10556788.2010.549231",
language = "English",
volume = "26",
pages = "873--894",
journal = "Optimization Methods and Software",
publisher = "Taylor & Francis",
number = "4-5",
}