Minimization algorithms based on supervisor and searcher cooperation

Authors
Citation
W. Liu et Yh. Dai, Minimization algorithms based on supervisor and searcher cooperation, J OPTIM TH, 111(2), 2001, pp. 359-379
Citations number
22
Categorie Soggetti
Engineering Mathematics
Journal title
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
ISSN journal
00223239 → ACNP
Volume
111
Issue
2
Year of publication
2001
Pages
359 - 379
Database
ISI
SICI code
0022-3239(200111)111:2<359:MABOSA>2.0.ZU;2-4
Abstract
In the present work, we explore a general framework for the design of new m inimization algorithms with desirable characteristics, namely, supervisor-s earcher cooperation. We propose a class of algorithms within this framework and examine a gradient algorithm in the class. Global convergence is estab lished for the deterministic case in the absence of noise and the convergen ce rate is studied. Both theoretical analysis and numerical tests show that -the algorithm is efficient for the deterministic case. Furthermore, the fa ct that there is no line search procedure incorporated in the algorithm see ms to strengthen its robustness so that it tackles effectively test problem s with stronger stochastic noises. The numerical results for both determini stic and stochastic test problems illustrate the appealing attributes of th e algorithm.