Title: The watchdog technique for forcing convergence in algorithms for constrained optimization
Abstract: The watchdog technique is an extension to iterative optimization algorithms that use line searches. The purpose is to allow some iterations to choose step-lengths that are much longer than those that would be allowed normally by the line search objective function. Reasons for using the technique are that it can give large gains in efficiency when a sequence of steps has to follow a curved constraint boundary, and it provides some highly useful algorithms with a Q-superlinear rate of convergence. The watchdog technique is described and discussed, and some global and Q-superlinear convergence properties are proved.
Publication Year: 1982
Publication Date: 1982-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
Access and Citation
Cited By Count: 309
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot