MALLBA: a library of skeletons for combinatorial optimisation

The MALLBA project tackles the resolution of combinatorial optimization problems using algorithmic skeletons implemented in C++. MALLBA offers three families of generic resolution methods: exact, heuristic and hybrid. Moreover, for each resolution method, MALLBA provides three different implementati...

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Detalles Bibliográficos
Autores: Alba, E, Almeida, F, Blesa Aguilera, Maria Josep|||0000-0001-8246-9926, Cabeza, J, Cotta, C, Díaz, M, Dorta, I, Gabarró Vallès, Joaquim|||0000-0003-3771-2813, León, C, Luna Garcia, Jesus, Moreno Boronat, Lidia Ana, Pablos, C, Petit Silvestre, Jordi|||0000-0001-8331-8126, Rojas Espinosa, Alfonso|||0000-0002-2630-4438, Xhafa Xhafa, Fatos|||0000-0001-6569-5497
Tipo de recurso: informe técnico
Fecha de publicación:2002
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/97560
Acceso en línea:https://hdl.handle.net/2117/97560
Access Level:acceso abierto
Palabra clave:MALLBA
Combinatorial optimization
Skeletons library
Àrees temàtiques de la UPC::Informàtica
Descripción
Sumario:The MALLBA project tackles the resolution of combinatorial optimization problems using algorithmic skeletons implemented in C++. MALLBA offers three families of generic resolution methods: exact, heuristic and hybrid. Moreover, for each resolution method, MALLBA provides three different implementations: sequential, parallel for local area networks, and parallel for wide area networks (currently under development). This paper shows the architecture of the MALLBA library, presents some of its skeletons and offers several computational results to show the viability of the approach.