Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autor principal: Tunçel, Levent
Lenguaje:eng
Publicado: American Mathematical Society 2010
Materias:
Acceso en línea:http://cds.cern.ch/record/2264203
_version_ 1780954335889326080
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