Abstract
Pheromone-based heuristic column generation (ACO-HCG) is a hybrid algorithm that combines ant colony optimization and a MIP solver to tackle vehicle routing problems (VRP) with black-box feasibility. Traditionally, the experimental analysis of such a complex algorithm has been carried out manually by trial and error. Moreover, a full-factorial statistical analysis is infeasible due to the large number of parameters and the time required for each algorithm run. In this paper, we first automatically configure the algorithm parameters by using an automatic algorithm configuration tool. Then, we perform a basic sensitivity analysis of the tuned configuration in order to understand the significance of each parameter setting. In this way, we avoid wasting effort analyzing parameter settings that do not lead to a high-performing algorithm. Finally, we show that the tuned parameter settings improve the performance of ACO-HCG on the multi-pile VRP and the three-dimensional loading capacitated VRP.
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
Balaprakash, P., Birattari, M., Stützle, T.: Improvement strategies for the F-race algorithm: Sampling design and iterative refinement. In: Bartz-Beielstein, T., Blesa Aguilera, M.J., Blum, C., Naujoks, B., Roli, A., Rudolph, G., Sampels, M. (eds.) HM 2007. LNCS, vol. 4771, pp. 108–122. Springer, Heidelberg (2007)
Birattari, M.: Tuning Metaheuristics: A Machine Learning Perspective. SCI, vol. 197. Springer, Heidelberg (2009)
Bortfeldt, A.: A hybrid algorithm for the capacitated vehicle routing problem with three-dimensional loading constraints. Comp. & Op. Res. 39(9), 2248–2257 (2012)
Doerner, K.F., Fuellerer, G., Hartl, R.F., Gronalt, M., Iori, M.: Metaheuristics for the vehicle routing problem with loading constraints. Networks 49(4), 294–307 (2007)
Dorigo, M., Stützle, T.: Ant Colony Optimization. MIT Press (2004)
Fuellerer, G., Doerner, K.F., Hartl, R.F., Iori, M.: Metaheuristics for vehicle routing problems with three-dimensional loading constraints. EJOR 201(3), 751–759 (2010)
Gendreau, M., Iori, M., Laporte, G., Martello, S.: A tabu search algorithm for a routing and container loading problem. Trans. Sci. 40(3), 342–350 (2006)
Hutter, F., Hoos, H.H., Leyton-Brown, K., Stützle, T.: ParamILS: an automatic algorithm configuration framework. Journal of Artificial Intelligence Research 36, 267–306 (2009)
Iori, M., Martello, S.: Routing problems with loading constraints. TOP 18, 4–27 (2010)
López-Ibáñez, M., Dubois-Lacoste, J., Stützle, T., Birattari, M.: The irace package, iterated race for automatic algorithm configuration. Tech. Rep. TR/IRIDIA/2011-004, IRIDIA, Université Libre de Bruxelles, Belgium (2011)
Massen, F., Deville, Y., Van Hentenryck, P.: Pheromone-based heuristic column generation for vehicle routing problems with black box feasibility. In: Beldiceanu, N., Jussien, N., Pinson, É. (eds.) CPAIOR 2012. LNCS, vol. 7298, pp. 260–274. Springer, Heidelberg (2012)
Prescott-Gagnon, E., Desaulniers, G., Drexl, M., Rousseau, L.M.: European driver rules in vehicle routing with time windows. Trans. Sci. 44(4), 455–473 (2010)
Reimann, M., Doerner, K., Hartl, R.F.: D-ants: Savings based ants divide and conquer the vehicle routing problem. Comp. & Op. Res. 31(4), 563–591 (2004)
Ren, J., Tian, Y., Sawaragi, T.: A relaxation method for the three-dimensional loading capacitated vehicle routing problem. In: 2011 IEEE/SICE International Symposium on System Integration (SII), pp. 750–755. IEEE (2011)
Ruan, Q., Zhang, Z., Miao, L., Shen, H.: A hybrid approach for the vehicle routing problem with three-dimensional loading constraints. Comp. & Op. Res. (2011)
Tarantilis, C., Zachariadis, E., Kiranoudis, C.: A hybrid metaheuristic algorithm for the integrated vehicle routing and three-dimensional container-loading problem. IEEE Transactions on Intelligent Transportation Systems 10(2), 255–271 (2009)
Toth, P., Vigo, D. (eds.): The Vehicle Routing Problem. SIAM Monographs on Discrete Mathematics and Applications (2002)
Tricoire, F., Doerner, K.F., Hartl, R.F., Iori, M.: Heuristic and exact algorithms for the multi-pile vehicle routing problem. OR Spectrum 33(4), 931–959 (2011)
Benchmark instances for the 3L-CVRP, http://www.or.deis.unibo.it/research.html
Benchmark instances for the MPVRP, http://prolog.univie.ac.at/research/VRPandBPP/
Supp. material, http://becool.info.ucl.ac.be/resources/ACO-HCG-IRACE
Zhu, W., Qin, H., Lim, A., Wang, L.: A two-stage tabu search algorithm with enhanced packing heuristics for the 3L-CVRP and M3L-CVRP. Comp. & Op. Res. 39(9), 2178–2195 (2012)
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
Massen, F., López-Ibáñez, M., Stützle, T., Deville, Y. (2013). Experimental Analysis of Pheromone-Based Heuristic Column Generation Using irace . In: Blesa, M.J., Blum, C., Festa, P., Roli, A., Sampels, M. (eds) Hybrid Metaheuristics. HM 2013. Lecture Notes in Computer Science, vol 7919. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38516-2_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-38516-2_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38515-5
Online ISBN: 978-3-642-38516-2
eBook Packages: Computer ScienceComputer Science (R0)