A Unified Approach to Global Convergence of Trust Region Methods for Nonsmooth Optimization
Date
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
This paper investigates the global convergence of trust region (TR) methods for solving nonsmooth minimization problems. For a class of nonsmooth objective functions called regular functions, conditions are found on the TR local models that imply three fundamental convergence properties. These conditions are shown to be satisfied by Fletcher's TR method for solving constrained optimization problems, Powell for solving nonlinear fitting problems, Zhang, Kim & Lasdon's successive linear programming method for solving constrained problems, Duff, Nocedal & Reid's TR method for solving systems of nonlinear equations, and El Hallabi & Tapia's TR method for solving systems of nonlinear equations. Thus our results can be viewed as a unified convergence theory for TR methods for nonsmooth problems.
Description
Advisor
Degree
Type
Keywords
Citation
Dennis, J.E. Jr., Li, Shou-Bai and Tapia, R.A.. "A Unified Approach to Global Convergence of Trust Region Methods for Nonsmooth Optimization." (1989) https://hdl.handle.net/1911/101657.