Result: Global optimization and constraint satisfaction: The branch-and-reduce approach

Title:
Global optimization and constraint satisfaction: The branch-and-reduce approach
Source:
Global optimization and constraint satisfaction (Valbonne-Sophia Antipolis, 2-4 October 2002, revised selected papers)Lecture notes in computer science. :1-16
Publisher Information:
Berlin: Springer, 2003.
Publication Year:
2003
Physical Description:
print, 46 ref
Original Material:
INIST-CNRS
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
University of Illinois, Department of Chemical and Biomolecular Engineering, Urbana, IL 61801, United States
ISSN:
0302-9743
Rights:
Copyright 2004 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

Operational research. Management
Accession Number:
edscal.15758842
Database:
PASCAL Archive

Further Information

In the early 1990s, we proposed the integration of constraint programming and optimization techniques within the branch-and-bound framework for the global optimization of nonconvex nonlinear and mixed-integer nonlinear programs. This approach, referred to as branch-and-reduce, was subsequently supplemented with a variety of branching and bounding schemes. In this paper, we review the theory and algorithms behind branch-and-reduce, its implementation in the BARON software, and some recent successful applications.