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The Vehicle Route Modeling and Optimization Considering the Dynamic Demands and Traffic Information

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Geo-Spatial Knowledge and Intelligence (GRMSE 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 698))

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Abstract

This paper is aimed to solve this kind of problem and cope with the actual requirements containing time window and dynamic demands. Therefore the smooth and continuous time dependent function is introduced and the two-stage model including the “initial optimization stage” and “real-time optimization stage” is established. At the same time, a hybrid algorithm based on genetic-tabu algorithm and simulated annealing algorithm is designed to solve the model. In the end the effectiveness of the hybrid algorithm and the model is verified by comparing the results of simulation and other algorithms.

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References

  1. Psaraftis, H.N.: A dynamic programming solution to the single vehicle many-to-many immediate request dial-a-ride problem. Transp. Sci. 14(2), 130–154 (1980)

    Article  Google Scholar 

  2. Haghani, A., Jung, S.: A dynamic vehicle routing problem with time-dependent travel times. Comput. Oper. Res. 32(11), 2959–2986 (2005)

    Article  MATH  Google Scholar 

  3. Hu, T., Liao, T., Lu, Y., et al.: A study on the solution approach for dynamic vehicle routing problems under real-time information. Transp. Res. Board Annu. Meet. 1857(1), 102–108 (2003)

    Article  Google Scholar 

  4. Li, B., Zheng, S.F., Cao, J.D., et al.: Method of solving vehicle routing problem with customers’ dynamic requests. J. Traffic Transp. Eng. (2007)

    Google Scholar 

  5. Zhou, B.: Research on vehicle routing problem with stochastic travel time. Dalian Maritime University (2005)

    Google Scholar 

  6. Lang, M.: Two-phase algorithm for dynamic distribution vehicle scheduling problem. J. Transp. Syst. Eng. Inf. Technol. 9(4), 140–144 (2009)

    Google Scholar 

  7. Mantawy, A.H., Abdelmagid, Y.L., Selim, S.Z.: Integrating genetic algorithms, Tabu search, and simulated annealing for the unit commitment problem. IEEE Trans. Power Syst. 14(3), 829–836 (1999)

    Article  Google Scholar 

  8. Hasan, M., Alkhamis, T., Ali, J.: A comparison between simulated annealing, genetic algorithm and Tabu search methods for the unconstrained quadratic Pseudo-Boolean function. Comput. Ind. Eng. 38(3), 323–340 (2000)

    Article  Google Scholar 

  9. Wang, X., Ge, X., Dai, Y.: Research on dynamic vehicle routing problem based on two-phase algorithm. Contl. Decis. 27(2), 175–181 (2012)

    MathSciNet  Google Scholar 

  10. Bin, W.U., Wei-Hong, N.I., Fan, S.H.: Particle swarm optimization for open vehicle routing problem in dynamic network. Comput. Integr. Manuf. Syst. 15(9), 1788–1794 (2009)

    Google Scholar 

  11. Yu, D., Zhang, Q., Yi, H.: New genetic algorithm syncretized the mi proved simulated annealing. J. Comput. Appl. 25(10), 2392–2394 (2005)

    Google Scholar 

  12. Huang, T., Gui, W., Yang, C.: Simulated annealing genetic hybrid algorithm and its applications, pp. 641–645 (2000)

    Google Scholar 

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Acknowledgment

Supported by the National Natural Science Foundation of China (71171070, U1509220).

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Authors and Affiliations

  1. Management School, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China

    Chouyong Chen & Jun Chen

Authors
  1. Chouyong Chen
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  2. Jun Chen
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Corresponding author

Correspondence to Chouyong Chen .

Editor information

Editors and Affiliations

  1. Beijing Institute of Technology, Beijing, China

    Hanning Yuan

  2. Beijing Institute of Technology, Beijing, China

    Jing Geng

  3. Wuhan University, Wuhan, China

    Fuling Bian

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Chen, C., Chen, J. (2017). The Vehicle Route Modeling and Optimization Considering the Dynamic Demands and Traffic Information. In: Yuan, H., Geng, J., Bian, F. (eds) Geo-Spatial Knowledge and Intelligence. GRMSE 2016. Communications in Computer and Information Science, vol 698. Springer, Singapore. https://doi.org/10.1007/978-981-10-3966-9_3

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  • DOI: https://doi.org/10.1007/978-981-10-3966-9_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3965-2

  • Online ISBN: 978-981-10-3966-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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