A Memetic algorithm for the minimum weighted k-cardinality tree subgraph problem

In this paper we present a memetic algorithm for the minimum weighted k-cardinality tree subgraph problem. This problem consists in finding, in a given undirected weighted graph G=(V,E,W), a tree T of k edges having minimal total weight among all of k-trees that are subgraphs of G. This problem was...

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Detalles Bibliográficos
Autores: Blesa Aguilera, Maria Josep|||0000-0001-8246-9926, Moscato, Pablo, Xhafa Xhafa, Fatos|||0000-0001-6569-5497
Tipo de recurso: informe técnico
Fecha de publicación:2001
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:2117/97659
Acceso en línea:https://hdl.handle.net/2117/97659
Access Level:acceso abierto
Palabra clave:Memetic algorithm
Minimum weighted k-cardinality tree subgraph problem
Àrees temàtiques de la UPC::Informàtica
Descripción
Sumario:In this paper we present a memetic algorithm for the minimum weighted k-cardinality tree subgraph problem. This problem consists in finding, in a given undirected weighted graph G=(V,E,W), a tree T of k edges having minimal total weight among all of k-trees that are subgraphs of G. This problem was first described by Hamacher, Jornsten, and Maffioli (1991) who also proved to be strongly NP-hard. Given this observation, researchers have focused on heuristic and metaheuristic algorithms to find suboptimal feasible solutions for the problem, as a good way to cope with most practical setting applications. To our knowledge, no memetic algorithm (MA) has yet been reported for this problem. It is known that some MAs have a good synergy with Tabu Search when they use it as individual steps for diversification and local optimization by the agents. As a consequence, one of our main motivations was to obtain a new implementation of an MA to the problem using an existing implementation of Tabu Search to the problem (Blesa and Xhafa, 2000). We are currently implementing the proposed algorithm.