Abstract
In this paper we deal with a capacitated asymmetric allocation hub location problem (CAAHLP). We determine the number of hubs, the locations of hubs, and asymmetric allocation of non-hub nodes to hub with the objective of minimum total transportation costs satisfying the required service level. To solve the problem optimally, we present a 0-1 integer programming model and find an optimal solution using CPLEX. As the CAAHLP has impractically demanding for the large-sized problem, a solution method based on combined ant colony optimization algorithm and genetic algorithm is developed which solve hub location problem and node allocation problem respectively. We investigate performance of the proposed solution method through the comparative study.
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References
Ernst, A.T., Krishnamoorthy, M.: Efficient algorithms for the uncapacitated single allocation p-hub median problem. Location Science 4, 139–154 (1996)
Campbell, J.F.: Integer programming formulation of discrete hub location problems. European Journal of Operational Research 72, 387–405 (1994)
Ebery, J., Krishnamoorthy, M., Ernst, A., Boland, N.: The capacitated multiple allocation hub location problem: Formulations and algorithms. European Journal of Operational Research 120, 614–631 (2000)
Chamberland, S., Sanso, B., Marcotte, O.: Topological design of two-level telecommunication networks with modular switches. Operations Research 48, 745–760 (2000)
Ernst, A.T., Krishnamoorthy, M.: Solution algorithms for the capacitated single allocation hub location problem. Annals of operations Research 86, 141–159 (1999)
Randall, M.: Solution approaches for the capacitated single allocation hub location problem using ant colony optimization. Computational Optimization and Applications 39, 239–261 (2008)
Dorigo, M., Stutzle, T.: Ant Colony Optimization. MIT Press, Boston (2004)
Ma, K.T., Ting, C.J.: An ant colony optimization algorithm for solving the uncapacitated multiple allocation p-hub median problem. In: Proceedings of the 9th Asia Pacific Industrial Engineering & Management Systems Conference, pp. 61–71. APIEMS, Bali (2008)
Helm, A.S.: A hybrid heuristic for the uncapacitated hub location problem. Journal of operational Research 106, 489–499 (1998)
Topcuoglu, H., Corut, F., Ermis, M., Yilmaz, G.: Solving the uncapacitated hub location problem using genetic algorithms. Computers & Operations Research 32, 967–984 (2005)
Kratica, J., Stanimirovic, Z.: Solving the uncapacitated multiple allocation p-hub center problem by genetic algorithm. Asia-Pacific Journal of Operational Research 23, 425–437 (2006)
Hwang, H., Sun, J.U.: A genetic-algorithm-based heuristic for the GT cell formation problem. Computers and Industrial Engineering 30, 941–955 (1996)
Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley, MA (1989)
Beasley, J.E.: Distributing test problems by electronic mail. Journal of the Operational Research Society 41, 1069–1072 (1990)
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Sun, J.U., Park, DH. (2012). An Ant Colony System Hybridized with a Genetic Algorithm for the Capacitated Hub Location Problem. In: Lee, G., Howard, D., Kang, J.J., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2012. Lecture Notes in Computer Science, vol 7425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32645-5_22
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DOI: https://doi.org/10.1007/978-3-642-32645-5_22
Publisher Name: Springer, Berlin, Heidelberg
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