DocumentCode :
1295039
Title :
Benchmarking a Wide Spectrum of Metaheuristic Techniques for the Radio Network Design Problem
Author :
Mendes, Sílvio P. ; Molina, Guillermo ; Vega-Rodríguez, Miguel A. ; Gómez-Pulido, Juan A. ; Sáez, Yago ; Miranda, Gara ; Segura, Carlos ; Alba, Enrique ; Isasi, Pedro ; León, Coromoto ; Sánchez-Pérez, Juan M.
Author_Institution :
Dept. of Comput. Sci., Polytech. Inst. of Leiria, Leiria, Portugal
Volume :
13
Issue :
5
fYear :
2009
Firstpage :
1133
Lastpage :
1150
Abstract :
The radio network design (RND) is an NP-hard optimization problem which consists of the maximization of the coverage of a given area while minimizing the base station deployment. Solving RND problems efficiently is relevant to many fields of application and has a direct impact in the engineering, telecommunication, scientific, and industrial areas. Numerous works can be found in the literature dealing with the RND problem, although they all suffer from the same shortfall: a noncomparable efficiency. Therefore, the aim of this paper is twofold: first, to offer a reliable RND comparison base reference in order to cover a wide algorithmic spectrum, and, second, to offer a comprehensible insight into accurate comparisons of efficiency, reliability, and swiftness of the different techniques applied to solve the RND problem. In order to achieve the first aim we propose a canonical RND problem formulation driven by two main directives: technology independence and a normalized comparison criterion. Following this, we have included an exhaustive behavior comparison between 14 different techniques. Finally, this paper indicates algorithmic trends and different patterns that can be observed through this analysis.
Keywords :
optimisation; radio networks; telecommunication network planning; NP-hard optimization problem; comparison base reference; coverage maximization; metaheuristic techniques; radio network design; Antennae; benchmarking; evolutionary algorithms; metaheuristics; optimization; radio network design (RND);
fLanguage :
English
Journal_Title :
Evolutionary Computation, IEEE Transactions on
Publisher :
ieee
ISSN :
1089-778X
Type :
jour
DOI :
10.1109/TEVC.2009.2023448
Filename :
5200350
Link To Document :
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