Abstract
Many optimization problems are dynamic, which means that the available data may change while the problem is being solved. Incorporating elements into the algorithm that take into account these changes usually leads to more effective algorithms which provide better solutions. In this work, we propose a flexibility strategy for the Vehicle Routing Problem with Dynamic Requests. We show that early decissions, which are taken in the beginning of the optimization process, influence the quality of final solutions for the dynamic problem. Our flexible algorithm provides better results than the canonical one and is competitive with the results in the literature.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
We’re sorry, something doesn't seem to be working properly.
Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.
References
Branke, J., Mattfeld, D.C.: Anticipation and flexibility in dynamic scheduling. International Journal of Production Research 43(15), 3103–3129 (2005)
Dantzig, G., Ramser, J.: The truck dispatching problem. Operations Research, Management Sciences 6(1), 80–91 (1959)
Francis, P., Smilowitz, K., Tzur, M.: The period vehicle routing problem with service choice. Transportation Science 40, 439–454 (2006)
Hansen, P., Mladenović, N.: An introduction to variable neighborhood search. In: Metaheuristics: Advances and Trends in Local Search Paradigms for Optimization, ch. 30, pp. 433–458. Kluwer Academic Publishers, Dordrecht (1999)
Hanshar, F., Ombuki-Berman, B.: Dynamic vehicle routing using genetic algorithms. Applied Intelligence 27, 89–99 (2007)
Hashimoto, H., Ibaraki, T., Imahori, S., Yagiura, M.: The VRP with flexible time windows and traveling times. Discrete Appl. Math. 154, 2271–2290 (2006)
Jans, R., Degraeve, Z.: Meta-heuristics for dynamic lot sizing: A review and comparison of solution approaches. European Journal of Operational Research 177(3), 1855–1875 (2007)
Khouadjia, M., Alba, E., Jourdan, L., Talbi, E.G.: Multi-swarm optimization for dynamic combinatorial problems: A case study on dynamic vehicle routing problem. In: Dorigo, M., Birattari, M., Di Caro, G.A., Doursat, R., Engelbrecht, A.P., Floreano, D., Gambardella, L.M., Groß, R., Şahin, E., Sayama, H., Stützle, T. (eds.) ANTS 2010. LNCS, vol. 6234, pp. 227–238. Springer, Heidelberg (2010)
Kilby, P., Prosser, P., Shaw, P.: Dynamic VRPs: A study of scenarios. APES-06-1998, University of Strathclyde, U.K (1998)
Kok, A., Meyer, C., Kopfer, H., Schutten, J.: A dynamic programming heuristic for the vehicle routing problem with time windows and the european community social legislation. Transportation Science (2010)
Montemanni, R., Gambardella, L., Rizzoli, A., Donati, A.: A new algorithm for a dynamic vehicle routing problem based on ant colony system. Journal of Combinatorial Optimization 10, 327–343 (2005)
Psaraftis, H.: Dynamic vehicle routing: status and prospects. Annals of Opertations Reasearch 61, 143–164 (1995)
Scheffermann, R., Bender, M., Cardeneo, A.: Robust solutions for vehicle routing problems via evolutionary multiobjective optimization. In: Proceedings of the 11th Congress on Evolutionary Computation, pp. 1605–1612 (2009)
Snoek, M.: Anticipation optimization in dynamic job shops. In: Proceedings of the 2001 Genetic and Evolutionary Computation Conference (2001)
Sörensen, K.: A framework for robust and flexible optimization using meta-heuristics with applications in supply chain design. Ph.D. thesis, Antwerp (2003)
Sörensen, K., Sevaux, M.: A practical approach for robust and flexible vehicle routing using metaheuristics and monte carlo sampling. Journal of Mathematical Modelling and Algorithms 8, 387–407 (2009)
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
Sarasola, B., Khouadjia, M.R., Alba, E., Jourdan, L., Talbi, EG. (2011). Flexible Variable Neighborhood Search in Dynamic Vehicle Routing. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2011. Lecture Notes in Computer Science, vol 6624. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20525-5_35
Download citation
DOI: https://doi.org/10.1007/978-3-642-20525-5_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20524-8
Online ISBN: 978-3-642-20525-5
eBook Packages: Computer ScienceComputer Science (R0)