Abstract
Shuffled Frog Leaping Algorithm (SFLA), which was presented by Eusuff and Lansey, is a novel meta-heuristic optimization. In this study, an improved SFLA (ISFLA) which improves the leaping rule of frog by enlarging the leaping step size and adding leaping inertia component in the view of social behavior is proposed to solve the Multi-Depot Vehicle Routing Problem (MDVRP). Considering the MDVRP is combinatorial optimization problem, in which every dimension of solution is discrete, we present a novel real number encoding method of ISFLA for MDVRP. At the same time, the Extremal Optimization (EO) is introduced to ISFLA to further improve the local search ability. The results of experiments have shown the proposed algorithm possesses outstanding performance to solve the MDVRP.
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References
Boettcher, S., Percus, A.G.: Extremal Optimization: Methods derived from Co-Evolution. In: Proceedings of the Genetic and Evolutionary Computation Conference, New York, USA, pp. 101–106 (1999)
Crevier, B., Cordeau, J., Laporte, G.: The multi-depot vehicle routing problem with inter-depot routes. European Journal of Operational Research 176(2), 756–773 (2007)
Dantzig, G., Ramser, J.: The truck dispatching problem. Management Science 6(1), 80–91 (1959)
Eusuff, M., Lansey, K.: Optimization of Water Distribution Network Design Using the Shuffled Frog Leaping Algorithm. Journal of Water Resources Planning and Management 129(3), 10–25 (2003)
Ghoseiri, K., Ghannadpour, S.F.: A hybrid genetic algorithm for multi-depot homogenous locomotive assignment with time windows. Applied Soft Computing 10(1), 53–65 (2010)
Liu, R., Jiang, Z.B., Fung, R.Y.K., Chen, F., Liu, X.: Two-phase heuristic algorithms for full truckloads multi-depot capacitated vehicle routing problem in carrier collaboration. Computers & Operations Research 37(11), 950–959 (2010)
Luo, J.P., Chen, M.R., Li, X.: A Novel Hybrid Algorithm for Global Optimization Based on EO and SFLA. In: 2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA, pp. 1935–1939 (2009)
Mirabi, M., Fatemi Ghomi, S.M.T., Jolai, F.: Efficient stochastic hybrid heuristics for the multi-depot vehicle routing problem. Robotics and Computer-Integrated Manufacturing 26(6), 564–569 (2010)
Villegas, J.G., Christian, P.: GRASP/VND and multi-start evolutionary local search for the single truck and trailer routing problem with satellite depots. Engineering Applications of Artificial Intelligence 23(5), 780–794 (2010)
Wren, A., Holliday, A.: Computer scheduling of vehicles from one or more depots to a number of delivery points. Operational Research Quarterly 23(3), 333–344 (1972)
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Luo, J., Li, X., Chen, MR. (2012). A Novel Meta-heuristic for the Multi-depot Vehicle Routing Problem. In: Liu, C., Wang, L., Yang, A. (eds) Information Computing and Applications. ICICA 2012. Communications in Computer and Information Science, vol 307. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34038-3_30
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DOI: https://doi.org/10.1007/978-3-642-34038-3_30
Publisher Name: Springer, Berlin, Heidelberg
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