Abstract
The Vehicle Routing Problem with Time Windows relates to frequently occuring real world problems in logistics. Much work has been done on solving static routing problems but solving the dynamic variants has not been given an equal amount of attention, while these are even more relevant to most companies in logistics and transportation. In this work an Ant Colony Optimization algorithm for solving the Dynamic Vehicle Routing Problem with Time Windows is proposed. Customers and time windows are inserted during the working day and need to be integrated in partially committed solutions. Results are presented on a benchmark that generalizes Solomon’s classical benchmark with varying degrees of dynamicity and different variants, including pheromone preservation and the min-max ant system.
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.
References
Bell, J.E., McMullen, P.R.: Ant colony optimization techniques for the vehicle routing problem. Advanced Engineering Informatics 18(1), 41–48 (2004)
Clarke, G., Wright, J.W.: Scheduling of vehicles from a central depot to a number of delivery points. Operations Research 12(4), 568–581 (1964)
Colorni, A., Dorigo, M., Maniezzo, V.: Distributed optimization by ant colonies. In: Varela, F., Bourgine, P. (eds.) Proceedings of the First European Conference on Artificial Life, Paris, France, pp. 134–142. Elsevier (1991)
Dorigo, M., Gambardella, L.M.: Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation 1(1), 53–66 (1997)
Eyckelhof, C.J., Snoek, M.: Ant systems for a dynamic TSP. In: Dorigo, M., Di Caro, G.A., Sampels, M. (eds.) ANTS 2002. LNCS, vol. 2463, pp. 88–99. Springer, Heidelberg (2002)
Flood, M.M.: The traveling-salesman problem. Operations Research 4(1), 61 (1956)
Gambardella, L.M., Taillard, É., Agazzi, G.: MACS-VRPTW: A multiple ant colony system for vehicle routing problems with time windows. In: New Ideas in Optimization, ch. 5, pp. 63–76. McGraw-Hill (1999)
Gendreau, M., Guertin, F., Potvin, J.-Y., Taillard, É.: Parallel tabu search for real-time vehicle routing and dispatching. Transportation Science 33(4), 381 (1999)
Guntsch, M., Middendorf, M.: Applying population based ACO to dynamic optimization problems. In: Dorigo, M., Di Caro, G.A., Sampels, M. (eds.) ANTS 2002. LNCS, vol. 2463, pp. 111–122. Springer, Heidelberg (2002)
Kilby, P., Prosser, P., Shaw, P.: Dynamic VRPs: a study of scenarios. Technical Report APES-06-1998, University of Strathclyde (September 1998)
Montemanni, R., Gambardella, L.M., Rizzoli, A.E., Donati, A.V.: Ant colony system for a dynamic vehicle routing problem. Journal of Combinatorial Optimization 10, 327–343 (2005)
Psaraftis, H.N.: Dynamic vehicle routing: Status and prospects. Annals of Operations Research 61, 143–164 (1995)
Solomon, M.M.: Algorithms for the vehicle routing and scheduling problems with time window constraints. Operations Research 35(2), 254–265 (1987)
Stützle, T., Hoos, H.: Max-min ant system and local search for the traveling salesman problem. In: IEEE International Conference on Evolutionary Computation, pp. 309–314 (April 1997)
Taillard, É., Badeau, P., Gendreau, M., Guertin, F., Potvin, J.-Y.: A tabu search heuristic for the vehicle routing problem with soft time windows. Transportation Science 31(2), 170 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
van Veen, B., Emmerich, M., Yang, Z., Bäck, T., Kok, J. (2013). Ant Colony Algorithms for the Dynamic Vehicle Routing Problem with Time Windows. In: Ferrández Vicente, J.M., Álvarez Sánchez, J.R., de la Paz López, F., Toledo Moreo, F.J. (eds) Natural and Artificial Computation in Engineering and Medical Applications. IWINAC 2013. Lecture Notes in Computer Science, vol 7931. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38622-0_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-38622-0_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38621-3
Online ISBN: 978-3-642-38622-0
eBook Packages: Computer ScienceComputer Science (R0)