Abstract
In the last decades a large amount of interests have been focused on telecommunication network problems. One important problem in telecommunication networks is the terminal assignment problem. In this paper, we propose a Differential Evolution algorithm employing a “multiple” strategy to solve the Terminal Assignment problem. A set of available strategies is established initially. In each generation a strategy is selected based on the amount fitness improvements achieved over a number of previous generations. We use tournament selection for this purpose. Simulation results with the different methods implemented are compared.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Salcedo-Sanz, S., Yao, X.: A hybrid Hopfield network-genetic algorithm approach for the terminal assignment problem. IEEE Transaction on Systems, Man and Cybernetics, 2343–2353 (2004)
Yao, X., Wang, F., Padmanabhan, K., Salcedo-Sanz, S.: Hybrid evolutionary approaches to terminal assignment in communications networks. In: Recent Advances in Memetic Algorithms and related search technologies, vol. 166, pp. 129–159. Springer, Berlin (2005)
Khuri, S., Chiu, T.: Heuristic Algorithms for the Terminal Assignment Problem. In: Proc. of the ACM Symposium on Applied Computing, pp. 247–251. ACM Press, New York (1997)
Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing. Springer, Berlin (2003)
Bernardino, E., Bernardino, A., Sánchez-Pérez, J., Vega-Rodríguez, M., Gómez-Pulido, J.: A Hybrid Differential Evolution Algorithm for solving the Terminal assignment problem. In: International Symposium on Distributed Computing and Artificial Intelligence, pp. 178–185. Springer, Heidelberg (2009)
Storn, R., Price, K.: Differential Evolution - a Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces. Technical Report TR-95-012, ICSI (1995)
Abuali, F., Schoenefeld, D., Wainwright, R.: Terminal assignment in a Communications Network Using Genetic Algorithms. In: Proc. of the 22nd Annual ACM Computer Science Conference, pp. 74–81. ACM Press, New York (1994)
Storn, R., Price, K.: Differential Evolution - a Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global Optimization 11, 341–359 (1997)
Differential Evolution Homepage, http://www.icsi.berkeley.edu/~storn/code.html
Bernardino, E., Bernardino, A., Sánchez-Pérez, J., Vega-Rodríguez, M., Gómez-Pulido, J.: Tabu Search vs Hybrid Genetic Algorithm to solve the terminal assignment problem. In: IADIS International Conference Applied Computing, pp. 404–409. IADIS Press (2008)
Xu, Y., Salcedo-Sanz, S., Yao, X.: Non-standard cost terminal assignment problems using tabu search approach. In: IEEE Conference in Evolutionary Computation, vol. 2, pp. 2302–2306 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bernardino, E.M., Bernardino, A.M., Sánchez-Pérez, J.M., Gómez-Pulido, J.A., Vega-Rodríguez, M.A. (2010). A Hybrid DE Algorithm with a Multiple Strategy for Solving the Terminal Assignment Problem. In: Konstantopoulos, S., Perantonis, S., Karkaletsis, V., Spyropoulos, C.D., Vouros, G. (eds) Artificial Intelligence: Theories, Models and Applications. SETN 2010. Lecture Notes in Computer Science(), vol 6040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12842-4_34
Download citation
DOI: https://doi.org/10.1007/978-3-642-12842-4_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12841-7
Online ISBN: 978-3-642-12842-4
eBook Packages: Computer ScienceComputer Science (R0)