Abstract
A hybrid Quantum-Inspired Evolutionary Algorithm (HQEA) with 2-OPT sub-routes optimization for capacitated vehicle routing problem (CVRP) is proposed. In the HQEA, 2-OPT algorithm is used to optimize sub-routes for convergence acceleration. Moreover, an encoding method of converting Q-bit representation to integer representation is designed. And genetic operators of quantum crossover and quantum variation are applied to enhance exploration. The proposed HQEA is tested based on classical benchmark problems of CVRP. Simulation results and comparisons with genetic algorithm show that the proposed HQEA has much better exploration quality and it is an effective method for CVRP.
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
Dantzig, G., Ramser, J.: The Truck Dispatching Problem[J]. Management Science (6), 80–91 (1959)
Zhang, L.P., Chai, Y.T.: Improved Genetic Algorithm for Vehicle Routing Problem[J]. Systems Engineering- Theory & Practices 22(8), 79–84 (2002)
Zhao, Y.W., Wu, B.: Double Populations Genetic Algorithm for Vehicle Routing Problem [J]. Computer Integrated Manufacturing Systems 10(3), 303–306 (2004)
Wu, B., Zhao, Y.W., Wang, W.L., et al.: Particle Swarm Optimization for Vehicle Routing Problem [C]. In: The 5th World Congress on Intelligent Control and Automation, pp. 2219–2221 (2004)
Narayanan, A., Moore, M.: Quantum-Inspired Genetic Algorithms. In: Proc. of the 1996 IEEE Intl. Conf. on Evolutionary Computation (ICEC 1996), Nogaya, Japan, IEEE Press, Los Alamitos (1996)
Han, K.H.: Genetic Quantum Algorithm and its Application to Combinatorial Optimi-zation Problem. In: IEEE Proc. of the 2000 Congress on Evolutionary Computation, San Diego, USA. IEEE Press, Los Alamitos (2000)
Han, K.H., Kim, J.H.: Quantum-inspired Evolutionary Algorithm for a Class of Combinatorial Optimization [J]. IEEE Trans on Evolutionary Computation (2002)
Han, K.H., Kim, J.H.: Quantum-inspired Evolutionary Algorithms with a New Termination Criterion H, Gate, and Two-Phase Scheme [J]. IEEE Trans on Evolutionary Computation (2004)
Wang, L., Wu, H.: A Hybrid Quantum-inspired Genetic Algorithm for Flow Shop Scheduling. In: Huang, D.-S., Zhang, X.-P., Huang, G.-B. (eds.) ICIC 2005. LNCS, vol. 3645, pp. 636–644. Springer, Heidelberg (2005)
Jiang, D.L., Yang, X.L.: A Study on the Genetic Algorithm for Vehicle Routing Problem [J]. Systems Engineering-Theory & Practice 19(6), 44–45 (1999)
Jiang, C.H., Dai, S.G.: Hybrid Genetic Algorithm for Capacitated Vehicle Routing Problem. Computer Integrated Manufacturing Systems. 13(10), 2047–2052 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhang, JL., Zhao, YW., Peng, DJ., Wang, WL. (2008). A Hybrid Quantum-Inspired Evolutionary Algorithm for Capacitated Vehicle Routing Problem. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues. ICIC 2008. Lecture Notes in Computer Science, vol 5226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87442-3_5
Download citation
DOI: https://doi.org/10.1007/978-3-540-87442-3_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87440-9
Online ISBN: 978-3-540-87442-3
eBook Packages: Computer ScienceComputer Science (R0)