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Solving the Terminal Assignment Problem Using a Local Search Genetic Algorithm

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Solving the terminal assignment problem using a local search genetic algorithm.pdfTerminal assignment is an important issue in telecommunication networks optimization. The task here is to assign a given collection of terminals to a given collection of concentrators. The main objective is to minimize the link cost to form a network. This optimization task is an NP-complete problem. The intractability of this problem is a motivation for the pursuits of a local search genetic algorithm that produces approximate, rather than exact, solutions. In this paper, we explore one of the most successful emerging ideas combining local search with population-based search. Simulation results verify the effectiveness of the proposed method. The results show that our algorithm provides good solutions in a better running time.231.06 KBAdobe PDF Ver/Abrir

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Resumo(s)

Terminal assignment is an important issue in telecommunication networks optimization. The task here is to assign a given collection of terminals to a given collection of concentrators. The main objective is to minimize the link cost to form a network. This optimization task is an NP-complete problem. The intractability of this problem is a motivation for the pursuits of a local search genetic algorithm that produces approximate, rather than exact, solutions. In this paper, we explore one of the most successful emerging ideas combining local search with population-based search. Simulation results verify the effectiveness of the proposed method. The results show that our algorithm provides good solutions in a better running time.

Descrição

International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI 2008)

Palavras-chave

Terminal Assignment Problem Genetic Algorithm Local Search Algorithm

Contexto Educativo

Citação

Bernardino, E.M., Bernardino, A.M., Sánchez-Pérez, J.M., Gómez-Pulido, J.A., Vega-Rodríguez, M.A. (2009). Solving the Terminal Assignment Problem Using a Local Search Genetic Algorithm. In: Corchado, J.M., Rodríguez, S., Llinas, J., Molina, J.M. (eds) International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI 2008). Advances in Soft Computing, vol 50. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85863-8_27.

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Editora

Springer Berlin Heidelberg

Licença CC

Sem licença CC

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