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Polyhedral and semidefinite programming methods in combinatorial optimization
Since the early 1960s, polyhedral methods have played a central role in both the theory and practice of combinatorial optimization. Since the early 1990s, a new technique, semidefinite programming, has been increasingly applied to some combinatorial optimization problems. The semidefinite programmin...
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Lenguaje: | eng |
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American Mathematical Society
2010
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Acceso en línea: | http://cds.cern.ch/record/2264203 |
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author | Tunçel, Levent |
author_facet | Tunçel, Levent |
author_sort | Tunçel, Levent |
collection | CERN |
description | Since the early 1960s, polyhedral methods have played a central role in both the theory and practice of combinatorial optimization. Since the early 1990s, a new technique, semidefinite programming, has been increasingly applied to some combinatorial optimization problems. The semidefinite programming problem is the problem of optimizing a linear function of matrix variables, subject to finitely many linear inequalities and the positive semidefiniteness condition on some of the matrix variables. On certain problems, such as maximum cut, maximum satisfiability, maximum stable set and geometric r |
id | cern-2264203 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2010 |
publisher | American Mathematical Society |
record_format | invenio |
spelling | cern-22642032021-04-21T19:13:27Zhttp://cds.cern.ch/record/2264203engTunçel, LeventPolyhedral and semidefinite programming methods in combinatorial optimizationMathematical Physics and MathematicsSince the early 1960s, polyhedral methods have played a central role in both the theory and practice of combinatorial optimization. Since the early 1990s, a new technique, semidefinite programming, has been increasingly applied to some combinatorial optimization problems. The semidefinite programming problem is the problem of optimizing a linear function of matrix variables, subject to finitely many linear inequalities and the positive semidefiniteness condition on some of the matrix variables. On certain problems, such as maximum cut, maximum satisfiability, maximum stable set and geometric rAmerican Mathematical Societyoai:cds.cern.ch:22642032010 |
spellingShingle | Mathematical Physics and Mathematics Tunçel, Levent Polyhedral and semidefinite programming methods in combinatorial optimization |
title | Polyhedral and semidefinite programming methods in combinatorial optimization |
title_full | Polyhedral and semidefinite programming methods in combinatorial optimization |
title_fullStr | Polyhedral and semidefinite programming methods in combinatorial optimization |
title_full_unstemmed | Polyhedral and semidefinite programming methods in combinatorial optimization |
title_short | Polyhedral and semidefinite programming methods in combinatorial optimization |
title_sort | polyhedral and semidefinite programming methods in combinatorial optimization |
topic | Mathematical Physics and Mathematics |
url | http://cds.cern.ch/record/2264203 |
work_keys_str_mv | AT tuncellevent polyhedralandsemidefiniteprogrammingmethodsincombinatorialoptimization |