Abstract
This paper presents a multi-cellular-ant algorithm for large scale capacitated vehicle routing problem with restrictive vehicle capability. The problem is divided into corresponding smaller ones by a decomposition methodology. Relative relationship between subsystems will be solved through cooperative performance among cellular ants to avoid trivial solutions. The empirical results composed with adaptive ant colony algorithm and traditional collaboration show more efficiency and availability.
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
Santos, L., Coutinho-Rodrigues, J., Current, J.R.: An improved heuristic for the capacitated arc routing problem. In: Computers and Operations Research, pp. 2632–2637 (2009)
Borgulya, I.: An algorithm for the capacitated vehicle routing problem with route balancing. Central European Journal of Operations Research, DEC, 331–343 (2008)
Wang, C.-H., Lu, J.-Z.: An effective evolutionary algorithm for the practical capacitated vehicle routing problems. J. Intell. Manuf. 21, 363–375 (2010)
Ai, T.J., Kachitvichyanukul, V.: Particle swarm optimization and two solution representations for solving the capacitated vehicle routing problem. Computers and Industrial Engineering, 380–387 (2009)
Borgulya, I.: An algorithm for the capacitated vehicle routing problem with route balancing. Central European Journal of Operations Research 16, 331–343 (2008)
Yuvraj Gajpal, P.L.: Abad Multi-ant colony system(MACS) for a vehicle routing problem with backhauls. European Journal of Operational Research, 102–117 (2009)
Bermudez, C., Graglia, P., Stark, N., Salto, C., Alfonso, H.: Comparison of Recombination Operators in Panmictic and Cellular GAs to Solve a Vehicle Routing Problem. Inteligencia Artificial 46, 34–44 (2010)
Chen, Y., Liu, J.: An tree generation algorithm of undirected graphs. The application of Computer Engineer, 115–117 (2002)
Li, Y., Yin, Z.-m.: Techniques by compound branch and network ripping to find out all spanning trees of an undirected graph. Journal of Naval University of Engineering, 74–77 (2004)
Ng, A., Harada, D., Russell, S.: Policy invariance under reward transformations: theory and application to reward shaping. In: ICML 1999 (1999)
Xiang, Y.: Distributed structure verification in multiply sectioned Bayesian networks. In: Florida Artificial Intelligence Research Symposium, pp. 295–299 (1996)
Moere, A.V., Clayden, J.J.: Cellular ants: Combining ant-based clustering with cellular automata. In: International Conference on Tools with Artificial Intelligence ICTAI, pp. 177–184 (2005)
Yu, X.-H., Chen, G.-A., Cheng, S.-X.: Dynamic learning rate optimization of the backpropagation algorithm. In: IEEE Transactions on Neural Networks, 669–677 (1995)
Cao, X.-e., Chen, H.-f.: Perturbation realization, potentials and sensitivity analysis of Markov processes. IEEE Transactions of Automatic Control, 1382–1393 (1997)
Bagnell, J., Ng, A.: On local rewards and scaling distributed reinforcement learning. Neural Information Processing Systems (2006)
Dietterich, T.G.: Hierarchical reinforcement learning with the MAXQ value function decomposition. JAIR
Jiang, L.-y., Zhang, J., Zhong, S.-h.: (2007) Analysis of parameters in ant colony system. Computer Engineering and Applications, 31–36 (2000)
Lysgaard, J., Letchford, A.N., Eglese, R.W.: A new branch-and-cut algorithm for the capacitated vehicle routing problem. Mathematical Programming 100(2), 423–445 (2004)
Fukasawa, R., Longo, H., Lysgaard, J., de Aragao, M.P., Reis, M., Uchoa, E., Werneck, R.F.: Robust branch-and-cut-and-price for the capacitated vehicle routing problem. Mathematical Programming 106(3), 491–511 (2006)
Kytojoki, J., Nuortio, T., Braysy, O., Gendreau, M.: An efficient variable neighborhood search heuristic for very large scale vehicle routing problems. Computers and Operations Research 34(9), 2743–2757 (2007)
Mestera, D., Braysyb, O.: Active-guided evolution strategies for large-scale capacitated vehicle routing problems. Computers and Operations Research 34(10), 2964–2975 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, J., Chai, Y., Li, P., Yin, H. (2011). Multi-cellular-ant Algorithm for Large Scale Capacity Vehicle Route Problem. In: Tan, Y., Shi, Y., Chai, Y., Wang, G. (eds) Advances in Swarm Intelligence. ICSI 2011. Lecture Notes in Computer Science, vol 6728. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21515-5_31
Download citation
DOI: https://doi.org/10.1007/978-3-642-21515-5_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21514-8
Online ISBN: 978-3-642-21515-5
eBook Packages: Computer ScienceComputer Science (R0)