Abstract
We propose an evolutionary algorithm (EA) that applies to the capacitated vehicle routing problem (CVRP). The EA uses edge assembly crossover (EAX) which was originally designed for the traveling salesman problem (TSP). EAX can be straightforwardly extended to the CVRP if the constraint of the vehicle capacity is not considered. To address the constraint violation, the penalty function method with 2-opt and Interchange neighborhoods is incorporated into the EA. Moreover, a local search is also incorporated into the EA. The experimental results demonstrate that the proposed EA can effectively find the best-known solutions on Christofides benchmark. Moreover, our EA found ten new best solutions for Golden instances in a reasonable computation time.
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
Golden, B.L., Wasil, E.A., Kelly, J.P., Chao, I.M.: Metaheuristics in vehicle routing. In: Crainic, T.G, Laporte, C. (eds.) Fleet Management and Logistics, pp. 33–56. Kiuwer, Boston (1998)
Toth, P., Vigo, D.: The granular tabu search and its application to the Vehicle Routing problem, INFORMS Journal on Computating 15, 333– 346
Taillard, E.D.: Parallel Iterative Search Methods for Vehicle Routing Problems. Networks 23, 661–673 (1993)
Kelly, J., Xu, J.P.: A Network Flow-Based Tabu Search Heuristic for the Vehicle Routing Problem. Transportation Science 30, 379–393 (1996)
Mester, D., Braysy, O.: Active Guided Evolution Strategies for Large Scale Vehicle Routing Problems with Time Windows. In: Computers & Operations Research, vol. 32, pp. 1593–1614 (2005)
Prins, C.A: simple and effective evolutionary algorithm for the vehicle routing problem. In: Computers & Operations Research, vol. 31, pp. 1985–2002 (2004)
Alba, E., Dorronsoro, B.: Solving the Vehicle Routing Problem by Using Cellular Genetic Algorithms, Evolutionary Computation in Combinatorial Optimization - EvoCOP 2004. In: Gottlieb, J., Raidl, G.R. (eds.) EvoCOP 2004. LNCS, vol. 3004, pp. 11–20. Springer, Heidelberg (2004)
Cordeau, J.F., Gendreau, M., Hertz, A., Laporte, G., Sormany, J.S.: New Heuristics for the Vehicle Routing Problem. In: Langevin, A., Riopel, D. (eds.) Logistics Systems: Design and Optimization, pp. 279–297. Springer, New York (2005)
Nagata, Y., Kobayashi, S.: Edge Assembly Crossover: A High-power Genetic Algorithm for the Traveling Salesman Problem. In: Proc. of the 7th Int. Conference on Genetic Algorithms, pp. 450–457 (1997)
Nagata, Y.: Fast EAX algorithm Considering Population Diversity for Traveling Salesman Problems. In: Proc. of the 6th Int. Conf. on EvoCOP2006, pp. 171–182 (2006)
Nagata, Y.: New EAX crossover for large TSP instances. In: Runarsson, T.P., Beyer, H.-G., Burke, E., Merelo-Guervós, J.J., Whitley, L.D., Yao, X. (eds.) Parallel Problem Solving from Nature - PPSN IX. LNCS, vol. 4193, pp. 372–381. Springer, Heidelberg (2006)
Kindervater, A.P., Savelsbergh, W.P: In: Aarts, E., Lenstra, J.K. (eds.) Local Search in Combinatorial optimization. John Wiley & Son, Chichester (1997)
Christofides, N., Mingozzi, A., Toth, P.: The vehicle routing problem. In: Christofides, N., Mingozzi, A., Toth, P., Sandi, C. (eds.) Combinatorial Optimization, Wiley, Chichester (1979)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Nagata, Y. (2007). Edge Assembly Crossover for the Capacitated Vehicle Routing Problem. In: Cotta, C., van Hemert, J. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2007. Lecture Notes in Computer Science, vol 4446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71615-0_13
Download citation
DOI: https://doi.org/10.1007/978-3-540-71615-0_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71614-3
Online ISBN: 978-3-540-71615-0
eBook Packages: Computer ScienceComputer Science (R0)