Abstract
Terminal Assignment is an important problem in telecommunication networks. The main objective is to assign a given collection of terminals to a given collection of concentrators. In this paper, we propose a Discrete Differential Evolution (DDE) algorithm for solving the Terminal Assignment problem. Differential Evolution algorithm is an evolutionary computation algorithm. This method has proved to be of practical success in a variety of problem domains. However, it does not perform well on dealing with Terminal Assignment problem because it uses discrete decision variables. To remedy this, a DDE algorithm is proposed to solve this problem. The results are compared to those given by some existing heuristics. We show that the proposed DDE algorithm is able to achieve feasible solutions to Terminal Assignment instances, improving the results obtained by previous approaches.
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.
Similar content being viewed by others
References
Khuri, S., Chiu, T.: Heuristic Algorithms for the Terminal Assignment Problem. In: Proc. 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 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)
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)
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 2009, 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)
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)
Price, K., Storn, R., Lampinen, J.: Differential Evolution - A Practical Approach to Global Optimization. Springer, Berlin (2005)
Differential Evolution, http://www.icsi.berkeley.edu/~storn/code.html
Bernardino, E., Bernardino, A., Sánchez-Pérez, J., Vega-Rodríguez, M., Gómez-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)
Tasgetiren, M.F., Pan, Q.-K., Liang, Y.-C.: A discrete differential evolution algorithm for the single machine total weighted tardiness problem with sequence dependent setup times. Computers and Operations Research 36(6), 1900–1915 (2009)
Tasgetiren, M.F., Pan, Q.-K., Liang, Y.-C., Suganthan, P.N.: A discrete differential evolution algorithm for the total earliness and tardiness penalties with a common due date on a single machine. In: Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Scheduling (CISched 2007), pp. 271–278 (2007)
Tasgetiren, M.F., Pan, Q.-K., Suganthan, P.N., Liang, Y.-C.: A discrete differential evolution algorithm for the no-wait flowshop scheduling problem with total flowtime criterion. In: Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Scheduling (CISched 2007), pp. 251–258 (2007)
Tasgetiren, M.F., Pan, Q.-K., Liang, Y.-C.: A discrete differential evolution algorithm for single machine total weighted tardiness problem with sequence dependent setup times. In: IEEE Congress on Evolutionary Computation, pp. 2613–2620 (2008)
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)
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: 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)
Bernardino, E., Bernardino, A., Sánchez-Pérez, J., Vega-Rodríguez, M., Gómez-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)
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). Discrete Differential Evolution Algorithm for Solving the Terminal Assignment Problem. In: Schaefer, R., Cotta, C., Kołodziej, J., Rudolph, G. (eds) Parallel Problem Solving from Nature, PPSN XI. PPSN 2010. Lecture Notes in Computer Science, vol 6239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15871-1_24
Download citation
DOI: https://doi.org/10.1007/978-3-642-15871-1_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15870-4
Online ISBN: 978-3-642-15871-1
eBook Packages: Computer ScienceComputer Science (R0)