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Research on Logistics Distribution Vehicle Scheduling Algorithm Based on Cloud Computing

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Cyberspace Safety and Security (CSS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11982))

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A logistics distribution vehicle scheduling model under cloud computing environment is established based on the analysis of factors affecting resource scheduling. The order information and logistics distribution vehicle information processing are completed under the framework of cloud computing, so as to obtain the most reasonable logistics distribution plan. To solve the problem of vehicle allocation in logistics distribution, a distribution path algorithm model and a minimum delivery cost algorithm model are established to provide the best strategy for logistics distribution scheme.

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  1. He, S.: On designing of China’s E-commerce logistic model. J. Guangdong Bus. Coll. 2, 82–86 (2003)

    Google Scholar 

  2. Yang, L., Wu, S.: Study of logistics management model based on e-commerce. In: International Conference on Advanced Computer Theory and Engineering, Chengdu, China. IEEE Xplore (2010)

    Google Scholar 

  3. Zhang, X.: Joint distribution patterns and decision-making paths for terminal logistics: based on supply and demand analysis of electric business logistics and community service. Res. Financ. Econ. Issues (3), 123–128 (2013)

    Google Scholar 

  4. Gu, W., Zhang, Q., Wei, L.: Method of large-scale vehicle routing problem based on GIS. Chin. J. Manag. Sci. 01, 379–389 (2013)

    Google Scholar 

  5. Guan, J.: Strategy for development of joint distribution mode for e-businesses. Logist. Technol. 07, 74–75 (2015)

    Google Scholar 

  6. Wei, X., Yan, J., Wang, Y.: E-commerce Logistics. The People’s Posts and Telecommunication Press, Beijing (2008)

    Google Scholar 

  7. Zhang, Y., Li, Q.: Research on the selection of logistics distribution mode of B2C e-commerce enterprises. J. Hum 3, 187–192 (2015)

    Google Scholar 

  8. Zhu, L., Ma, Y., Ding, J.: Supernetwork-based vehicles cooperation optimization among logistics enterprises under low-carbon concept. Sci. Technol. Manag. Res. 36(24), 260–266 (2016)

    Google Scholar 

  9. Han, M., Wang, H.: Study of community E-commerce logistic distribution model based on intelligent community property. In: Li, X., Xu, X. (eds.) Proceedings of the Fourth International Forum on Decision Sciences. UOR, pp. 645–650. Springer, Singapore (2017).

    Chapter  Google Scholar 

  10. Ding, W.: Solving of emergency logistics vehicle routing problem with genetic algorithm under capacity constraints. Huazhong University of Science and Technology, Wuhan, pp. 61–76 (2013)

    Google Scholar 

  11. Ma, X., Li, H.: A new genetic algorithm for the capacity constraints vehicle routing problem. Adv. Appl. Math. 03, 222–230 (2014)

    Article  Google Scholar 

  12. Yang, Z.: Research on the multi-objective vehicle routing optimization in urban express distribution. Harbin Institute of Technology, Harbin, pp. 66–82 (2015)

    Google Scholar 

  13. Zhang, M.: Vehicle routing problems with uncertain factors. University of Science and Technology of China, Hefei, pp. 71–85 (2016)

    Google Scholar 

  14. Zhou, L., Lin, Y., Wang, X.: Integrated optimization for multiclass terminal location-heterogeneous vehicle routing of urban distribution under online shopping. Comput. Integr. Manuf. Syst. 22(4), 1139–1147 (2016)

    Google Scholar 

  15. Liu, Z.: The application of cloud computing in marine transportation logistics electronic management system. Ship Sci. Technol. 38(18), 103–105 (2016)

    Google Scholar 

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This work was supported in part by the Beijing Great Wall Scholars’ Program under Grant CIT and TCD20170317, in part by the Beijing Tongzhou Canal Plan “Leading Talent Plan”, in part by the Beijing Collaborative Innovation Center and in part by the Management Science and Engineering High-precision Project.

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Correspondence to Huwei Liu .

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Liu, H., Zhao, Y., Cao, N. (2019). Research on Logistics Distribution Vehicle Scheduling Algorithm Based on Cloud Computing. In: Vaidya, J., Zhang, X., Li, J. (eds) Cyberspace Safety and Security. CSS 2019. Lecture Notes in Computer Science(), vol 11982. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37336-8

  • Online ISBN: 978-3-030-37337-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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