Abstract
In this article we solve the radio network design problem (RND). This NP-hard combinatorial problem consist of determining a set of locations for placing radio antennae in a geographical area in order to offer high radio coverage using the smallest number of antennae. This problem is originally found in mobile telecommunications (such as mobile telephony), and is also relevant in the rising area of sensor networks. In this work we propose an evolutionary algorithm called CHC as the state of the art technique for solving RND problems and determine its expected performance for different instances of the RND problem.
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References
Matsui, S., Watanabe, I., Tokoro, K.: Application of the parameter-free genetic algorithm to the fixed channel assignment problem. Systems and Computers in Japan 36(4), 71–81 (2005)
Zappala, D.: Alternate Path Routing for Multicast. IEEE/ACM Transactions on Networking 12(1), 30–43 (2004)
Blum, C., Blesa, M.J., Roli, A.: Combining ILS with an effective constructive heuristic for the application to error correcting code design. In: Metaheuristics International Conference (MIC-2005), Viena, Austria, pp. 114–119 (2005)
Maple, C., Guo, L., Zhang, J.: Parallel genetic algorithms for third generation mobile network planning. In: Proceedings of the International Conference on Parallel Computing in Electrical Engineering (PARELEC 2004), pp. 229–236 (2004)
Créput, J., et al.: Automatic mesh generation for mobile network dimensioning using evolutionary approach. IEEE Trans. Evolutionary Computation 9(1), 18–30 (2005)
Calégari, P., et al.: Parallel island-based genetic algorithm for radio network design. Journal of Parallel and Distributed Computing 47, 86–90 (1997)
Alba, E., Chicano, F.: On the behavior of parallel genetic algorithms for optimal placement of antennae in telecommunications. International Journal of Foundations of Computer Science 16(2), 343–359 (2005)
Eshelman, L.J.: The CHC Adaptive Search Algorithm: How to Have Safe Search When Engaging in Nontraditional Genetic Recombination. In: Foundations of Genetic Algorithms, pp. 265–283. Morgan Kaufmann, San Francisco (1991)
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© 2007 Springer Berlin Heidelberg
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Alba, E., Molina, G., Chicano, F. (2007). Optimal Placement of Antennae Using Metaheuristics. In: Boyanov, T., Dimova, S., Georgiev, K., Nikolov, G. (eds) Numerical Methods and Applications. NMA 2006. Lecture Notes in Computer Science, vol 4310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70942-8_25
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DOI: https://doi.org/10.1007/978-3-540-70942-8_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70940-4
Online ISBN: 978-3-540-70942-8
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