Title
A nonmonotone trust region method with new inexact line search for unconstrained optimization
Abstract
In this paper, a new nonmonotone inexact line search rule is proposed and applied to the trust region method for unconstrained optimization problems. In our line search rule, the current nonmonotone term is a convex combination of the previous nonmonotone term and the current objective function value, instead of the current objective function value . We can obtain a larger stepsize in each line search procedure and possess nonmonotonicity when incorporating the nonmonotone term into the trust region method. Unlike the traditional trust region method, the algorithm avoids resolving the subproblem if a trial step is not accepted. Under suitable conditions, global convergence is established. Numerical results show that the new method is effective for solving unconstrained optimization problems.
Year
DOI
Venue
2013
10.1007/s11075-012-9652-0
Numerical Algorithms
Keywords
Field
DocType
Unconstrained optimization,Inexact line search,Trust region method,Global convergence,Numerical experiments
Convergence (routing),Trust region,Mathematical optimization,Convex combination,Line search,Optimization problem,Mathematics
Journal
Volume
Issue
ISSN
64
1
1017-1398
Citations 
PageRank 
References 
2
0.39
15
Authors
2
Name
Order
Citations
PageRank
Jinghui Liu120.39
Changfeng Ma219729.63