A hybrid grouping genetic algorithm for the multiple-type access node location problem

Authors:
O. Alonso-Garrido;S. Salcedo-Sanz;L. E. Agustín-Blas;E. G. Ortiz-García;A. M. Pérez-Bellido;J. A. Portilla-Figueras
Affiliations:
Department of Signal Theory and Communications, Universidad de Alcalá, Alcalá de Henares, Madrid, Spain;Department of Signal Theory and Communications, Universidad de Alcalá, Alcalá de Henares, Madrid, Spain;Department of Signal Theory and Communications, Universidad de Alcalá, Alcalá de Henares, Madrid, Spain;Department of Signal Theory and Communications, Universidad de Alcalá, Alcalá de Henares, Madrid, Spain;Department of Signal Theory and Communications, Universidad de Alcalá, Alcalá de Henares, Madrid, Spain;Department of Signal Theory and Communications, Universidad de Alcalá, Alcalá de Henares, Madrid, Spain
Venue:
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Year:
2009

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Abstract

This paper presents a new model for the access node location problem (ANLP) in communications networks, in which the access nodes (concentrators) can be chosen from different types (with different capacity and cost). The paper also proposes a hybrid grouping genetic algorithm which is able to efficiently solve the problem. In the paper, the main characteristics of the algorithm (encoding, operators and fitness function) are fully described, and its performance has been shown by solving different ANLP instances incorporating the new model.