A Nonmonotone Trust Region Method for Nonlinear Programming with Simple Bound Constraints

Journal Article · Sun Jul 01 00:00:00 EDT 2001 · Applied Mathematics and Optimization

DOI:https://doi.org/10.1007/S002450010020· OSTI ID:21067512

In this paper we propose a nonmonotone trust region algorithm for optimization with simple bound constraints. Under mild conditions, we prove the global convergence of the algorithm. For the monotone case it is also proved that the correct active set can be identified in a finite number of iterations if the strict complementarity slackness condition holds, and so the proposed algorithm reduces finally to an unconstrained minimization method in a finite number of iterations, allowing a fast asymptotic rate of convergence. Numerical experiments show that the method is efficient.

• OSTI ID: 21067512
• Journal Information: Applied Mathematics and Optimization, Journal Name: Applied Mathematics and Optimization Journal Issue: 1 Vol. 43; ISSN 0095-4616
• Country of Publication: United States
• Language: English

Related Subjects

71 CLASSICAL AND QUANTUM MECHANICS
GENERAL PHYSICS
ALGORITHMS
ASYMPTOTIC SOLUTIONS
CONVERGENCE
MINIMIZATION
NONLINEAR PROGRAMMING