Treffer: A relaxed cutting plane method for semi-infinite semi-definite programming

Title:
A relaxed cutting plane method for semi-infinite semi-definite programming
Source:
Journal of computational and applied mathematics. 196(2):459-473
Publisher Information:
Amsterdam: Elsevier, 2006.
Publication Year:
2006
Physical Description:
print, 17 ref
Original Material:
INIST-CNRS
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Information and Computer Sciences, College of Sciences, Chongqing University, Chongqing 400044, China
Institute of Applied Mathematics, National Cheng-Kung University, Tainan 700, Tawain, Province of China
Department of Applied Mathematics, The Hong Kong Polytechnic University, Kowloon, Hong-Kong
Department of Mathematics and Statistics, Curtin University of Technology, GPO Box U1987, Perth, W.A. 6845, Australia
ISSN:
0377-0427
Rights:
Copyright 2006 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:
Mathematics
Accession Number:
edscal.17991960
Database:
PASCAL Archive

Weitere Informationen

In this paper, we develop two discretization algorithms with a cutting plane scheme for solving combined semi-infinite and semi-definite programming problems, i.e., a general algorithm when the parameter set is a compact set and a typical algorithm when the parameter set is a box set in the m-dimensional space. We prove that the accumulation point of the sequence points generated by the two algorithms is an optimal solution of the combined semi-infinite and semi-definite programming problem under suitable assumption conditions. Two examples are given to illustrate the effectiveness of the typical algorithm.