Inner Approximation Method for a Reverse Convex Programming Problem

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. We propose an inner approximation method to solve the problem in the case where X is not necessarily a p...

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Veröffentlicht in:Journal of optimization theory and applications Jg. 107; H. 2; S. 355 - 389
Hauptverfasser: Yamada, S., Tanino, T., Inuiguchi, M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY Springer 01.11.2000
Springer Nature B.V
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ISSN:0022-3239, 1573-2878
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Abstract 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. We propose an inner approximation method to solve the problem in the case where X is not necessarily a polytope. The algorithm utilizes an inner approximation of X by a sequence of polytopes to generate relaxed problems. It is shown that every accumulation point of the sequence of optimal solutions of the relaxed problems is an optimal solution of the original problem.
AbstractList 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. We propose an inner approximation method to solve the problem in the case where X is not necessarily a polytope. The algorithm utilizes an inner approximation of X by a sequence of polytopes to generate relaxed problems. It is shown that every accumulation point of the sequence of optimal solutions of the relaxed problems is an optimal solution of the original problem.
Author Inuiguchi, M.
Yamada, S.
Tanino, T.
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  surname: Tanino
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  givenname: M.
  surname: Inuiguchi
  fullname: Inuiguchi, M.
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CitedBy_id crossref_primary_10_1016_S0377_0427_02_00418_1
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Cites_doi 10.1007/978-1-4615-2025-2
10.1515/9781400873173
10.1007/978-1-4757-2809-5
10.1007/978-3-662-03199-5
10.1137/1015073
10.1007/978-1-4615-4098-4
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Copyright Plenum Publishing Corporation 2000
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Penalty function
Global optimum
Duality
Convex programming
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Snippet 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...
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StartPage 355
SubjectTerms Algorithms
Applied sciences
Approximation
Engineering schools
Exact sciences and technology
Information systems
Mathematical functions
Mathematical programming
Operational research and scientific management
Operational research. Management science
Optimization
Title Inner Approximation Method for a Reverse Convex Programming Problem
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