Non-monotone trust-region algorithms for nonlinear optimization subject to convex constraints

Non-monotone trust-region algorithms for nonlinear optimization subject to convex constraints

0.00 Avg rating0 Votes
Article ID: iaor19981378
Country: Netherlands
Volume: 77
Issue: 1
Start Page Number: 69
End Page Number: 94
Publication Date: Apr 1997
Journal: Mathematical Programming
Authors:
Keywords: trust regions
Abstract:

This paper presents two new trust-region methods for solving nonlinear optimization problems over convex feasible domains. These methods are distinguished by the fact that they do not enforce strict monotonicity of the objective function values at successive iterates. The algorithms are proved to be convergent to critical points of the problem from any starting point. Extensive numerical experiments show that this approach is competitive with the LANCELOT package.

Reviews

Required fields are marked *. Your email address will not be published.