Abstract
The terminal assignment (TA) problem is an important problem in the design of telecommunication networks. The problem consists in determining the best links for connecting a given set of terminals to a given set of concentrators so that a given cost function is optimized. In this paper, we have proposed an artificial bee colony algorithm based approach for solving the TA problem. In comparison with the best methods available in the literature, the proposed approach obtained better quality solutions in shorter time.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Karaboga, D., Basturk, K.: On the performance of artificial bee colony (ABC) algorithm. Appl. Soft Comput. 8, 687–697 (2008)
Singh, A.: An artificial bee colony algorithm for the leaf constrained minimum spanning tree problem. Appl. Soft Comput. 9, 625–631 (2009)
Bernardino, E., Bernardino, A., Sanchez- Perez, J., Vega-Rodriguez, M., Gomez-Pulido, J.: Tabu search vs hybrid genetic algorithm to solve the terminal assignment problem. In: International Conference on Applied Computing, pp. 404–409 (2008)
Xu, Y., Salcedo-Sanz, S., Yao, X.: Non-standard cost terminal assignment problems using tabu search approach. IEEE Conf. Evol. Comput. 2, 2302–2306 (2004)
Bernardino, E., Bernardino, A., Sanchez-Perez, J., Vega-Rodriguez, M., Gomez-Pulido, J.: Solving the terminal assignment problem using a local search genetic algorithm. In: International Symposium on Distributed Computing and Artificial Intelligence, pp. 225–234, Springer, Heidelberg (2008)
Bernardino, E., Bernardino, A., Sanchez-Perez, J., Vega-Rodriguez, M., Gomez-Pulido, J.: A hybrid differential evolution algorithm with a multiple strategy for solving the terminal assignment problem. In: 6th Hellenic Conference on Artificial Intelligence. Springer, Heidelberg (2010)
Khuri, S., Chiu, T.: Heuristic algorithms for the terminal assignment problem. In: Proceedings of the ACM Symposium on Applied Computing, pp. 247–251 (1997)
Salcedo-Sanz, S., Yao, X.: A hybrid Hopfield network genetic algorithm approach for the terminal assignment problem. IEEE Trans. Syst. Man Cybern. 34(6), 2343–2353 (2004)
Abuali, F., Schoenefeld, D., Wainwright, R.: Terminal assignment in a communications network using genetic algorithms. In: Proceedings of the 22nd Annual ACM Computer Science Conference, pp. 74–81. ACM press, Newyork (1994)
Singh, A., Sunder, S.: An artificial bee colony algorithm for the minimum routing cost spanning tree problem. Soft Comput. 15, 2489–2499 (2011)
Bernardino, E.M., Bernardino, A.M., Sánchez-Pérez, J.M., Gómez-Pulido, J.A., Vega-RodrÃguez, M.A.: Discrete differential evolution algorithm for solving the terminal assignment problem. In: Schaefer, R., Cotta, C., KoÅ‚odziej, J., Rudolph, G. (eds.) PPSN XI. LNCS, vol. 6239, pp. 229–239. Springer, Heidelberg (2010)
Karaboga, D., Gorkemli, B., Ozturk, C., Karaboga, N.: A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artif. Intell. Rev. 42, 21–57 (2014)
Karaboga, D., Basturk, B.: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J. Global Optim. 39, 459–471 (2007)
Karaboga, D., Basturk, B.: Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems. In: Melin, P., Castillo, O., Aguilar, L.T., Kacprzyk, J., Pedrycz, W. (eds.) IFSA 2007. LNCS (LNAI), vol. 4529, pp. 789–798. Springer, Heidelberg (2007)
Bernardino, E.M., Bernardino, A.M., Sánchez-Pérez, J.M., Gómez-Pulido, J.A., Vega-RodrÃguez, M.A.: Using the bees algorithm to assign terminals to concentrators. In: GarcÃa-Pedrajas, N., Herrera, F., Fyfe, C., BenÃtez, J.M., Ali, M. (eds.) IEA/AIE 2010, Part II. LNCS, vol. 6097, pp. 267–276. Springer, Heidelberg (2010)
Bernardino, E.M., Bernardino, A.M., Sánchez-Pérez, J.M., Gómez-Pulido, J.A., Vega-RodrÃguez, M.A.: A Hybrid differential evolution algorithm for solving the terminal assignment problem. In: Omatu, S., Rocha, M.P., Bravo, J., Fernández, F., Corchado, E., Bustillo, A., Corchado, J.M. (eds.) IWANN 2009, Part II. LNCS, vol. 5518, pp. 179–186. Springer, Heidelberg (2009)
Pan, Q.-K., Tasgetiren, M. F., Liang, Y.C.: A discrete differential evolution algorithm for the permutation flowshop scheduling problem. In: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, pp. 126–133 (2007)
Pan, Q.-K., Tasgetiren, M.F., Suganthan, P.N., Chen, A.H.-L.: A discrete artificial bee colony algorithm for the total flowtime minimization in permutation flow shops. Inf. Sci. 181, 3459–3475 (2011)
Kershenbaum, A.: Telecommunications Network Design Algorithms. McGraw-Hill, New York (1993)
Bose, D., Kundu, S., Biswas, S., Das, S.: Circular antenna array design using novel perturbation based artificial bee colony algorithm. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Nanda, P.K. (eds.) SEMCCO 2012. LNCS, vol. 7677, pp. 459–466. Springer, Heidelberg (2012)
Biswas, S., Kundu, S., Bose, D., Das, S., Suganthan, P.N., Panigrahi, B.K.: Migrating forager population in a multi-population artificial bee colony algorithm with modified perturbation schemes. In: 2013 IEEE Symposium on Swarm Intelligence (SIS 2013), pp. 248–255 (2013)
Bose, D., Biswas, S., Vasilakos, A.V., Laha, S.: Optimal filter design using an improved artificial bee colony algorithm. Inf. Sci. 281, 443–461 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Banda, J., Singh, A. (2015). A Hybrid Artificial Bee Colony Algorithm for the Terminal Assignment Problem. In: Panigrahi, B., Suganthan, P., Das, S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2014. Lecture Notes in Computer Science(), vol 8947. Springer, Cham. https://doi.org/10.1007/978-3-319-20294-5_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-20294-5_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-20293-8
Online ISBN: 978-3-319-20294-5
eBook Packages: Computer ScienceComputer Science (R0)