2002年9月
An inner approximation method incorporating with a penalty function method for a reverse convex programming problem
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
- ,
- ,
- 巻
- 146
- 号
- 1
- 開始ページ
- 57
- 終了ページ
- 75
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1016/S0377-0427(02)00418-1
- 出版者・発行元
- ELSEVIER SCIENCE BV
In this paper, we consider a reverse convex programming problem constrained by a convex set and a reverse convex set which is defined by the complement of the interior of a compact convex set X. When X is not necessarily a polytope, an inner approximation method has been proposed (J. Optim. Theory Appl. 107(2) (2000) 357). The algorithm utilizes inner approximation of X by a sequence of polytopes to generate relaxed problems. Then, every accumulation point of the sequence of optimal solutions of relaxed problems is an optimal solution of the original problem. In this paper, we improve the proposed algorithm. By underestimating the optimal value of the relaxed problem, the improved algorithms have the global convergence. (C) 2002 Elsevier Science B.V. All rights reserved.
- リンク情報
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- DOI
- https://doi.org/10.1016/S0377-0427(02)00418-1
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000177564400007&DestApp=WOS_CPL
- URL
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=0036724615&origin=inward
- ID情報
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- DOI : 10.1016/S0377-0427(02)00418-1
- ISSN : 0377-0427
- SCOPUS ID : 0036724615
- Web of Science ID : WOS:000177564400007