Treffer: Numerical experiences with a new generalized subinterval selection criterion for interval global optimization

Title:
Numerical experiences with a new generalized subinterval selection criterion for interval global optimization
Authors:
Source:
Proceedings of the Validated Computing 2002 conference, May 23-25, 2002, Toronto, CanadaReliable computing. 9(2):109-125
Publisher Information:
Heidelberg: Springer, 2003.
Publication Year:
2003
Physical Description:
print, 19 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
University of Szeged, Department of Applied Informatics, P.O. Box 652, 6701 Szeged, Hungary
ISSN:
1385-3139
Rights:
Copyright 2003 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems

Mathematics
Accession Number:
edscal.14623467
Database:
PASCAL Archive

Weitere Informationen

The convergence properties are studied for interval global optimization algorithms that select the next subinterval to be subdivided with the largest value of the indicator pf(fk,X) = . In contrast to previous work, here the more general case is investigated, when the global minimum value is unknown, and thus its estimation fk in the iteration k has an important role. Extensive numerical tests on 40 problems confirm that substantial improvements can be achieved both on simple and sophisticated algorithms by the new method (not utilizing the minimum value).