Abstract
The vehicle routing problem with route balancing (VRPRB) is a variant of classical VRPs. It is a bi-objective optimization problem which considers the total length of routes and the balance issue among different routes. In this paper, the balance objective we introduce is the minimization of the maximal route length, which can effectively avoid the occurrence of distorted solutions. We develop an NSGA-II based memetic algorithm (M-NSGA-II) for the VRPRB. The M-NSGA-II algorithm combines the NSGA-II algorithm with a local search procedure which consists of four local search operators. To evaluate our algorithm, we test it on the standard benchmarks and compare our results with the referenced approach. Moreover, we analyze the effect of different local search operators on M-NSGA-II algorithm. Computational results indicate that our M-NSGA-II algorithm is able to produce better solutions.
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
References
Beasley, J.E.: Route firstcluster second methods for vehicle routing. Omega 11(4), 403–408 (1983)
Coello, C.A.C., Cortés, N.C.: Solving multiobjective optimization problems using an artificial immune system. Genet. Program. Evolvable Mach. 6(2), 163–190 (2005)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)
Garcia-Najera, A., Bullinaria, J.A.: Bi-objective optimization for the vehicle routing problem with time windows: using route similarity to enhance performance. In: Ehrgott, M., Fonseca, C.M., Gandibleux, X., Hao, J.-K., Sevaux, M. (eds.) EMO 2009. LNCS, vol. 5467, pp. 275–289. Springer, Heidelberg (2009). doi:10.1007/978-3-642-01020-0_24
Jozefowiez, N., Semet, F., Talbi, E.G.: An evolutionary algorithm for the vehicle routing problem with route balancing. Eur. J. Oper. Res. 195(3), 761–769 (2009)
Lacomme, P., Prins, C., Prodhon, C., Ren, L.: A multi-start split based path relinking (MSSPR) approach for the vehicle routing problem with route balancing. Eng. Appl. Artif. Intell. 38, 237–251 (2015)
Lee, T.R., Ueng, J.H.: A study of vehicle routing problems with load-balancing. Int. J. Phys. Distrib. Logistics Manage. 29(10), 646–657 (1999)
Mandal, S.K., Pacciarelli, D., Lkketangen, A., Hasle, G.: A memetic NSGA-II for the bi-objective mixed capacitated general routing problem. J. Heuristics 21(3), 359–390 (2015)
Melián-Batista, B., De Santiago, A., AngelBello, F., Alvarez, A.: A bi-objective vehicle routing problem with time windows: a real case in tenerife. Appl. Soft Comput. 17, 140–152 (2014)
Oyola, J., Løkketangen, A.: Grasp-ASP: an algorithm for the CVRP with route balancing. J. Heuristics 20(4), 361–382 (2014)
Pacheco, J., Caballero, R., Laguna, M., Molina, J.: Bi-objective bus routing: an application to school buses in rural areas. Transp. Sci. 47(3), 397–411 (2013)
Zitzler, E., Laumanns, M., Thiele, L., et al.: SPEA2: improving the strength pareto evolutionary algorithm. In: Eurogen, vol. 3242, pp. 95–100 (2001)
Acknowledgments
This research was partially supported by Guangdong Natural Science Funds (No. 2014A030310312, No. 2016A030313264) and National Natural Science Foundation of China (No. 61673403).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Sun, Y., Liang, Y., Zhang, Z., Wang, J. (2017). M-NSGA-II: A Memetic Algorithm for Vehicle Routing Problem with Route Balancing. In: Benferhat, S., Tabia, K., Ali, M. (eds) Advances in Artificial Intelligence: From Theory to Practice. IEA/AIE 2017. Lecture Notes in Computer Science(), vol 10350. Springer, Cham. https://doi.org/10.1007/978-3-319-60042-0_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-60042-0_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-60041-3
Online ISBN: 978-3-319-60042-0
eBook Packages: Computer ScienceComputer Science (R0)