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Optimization Scheduling Algorithm of Logistics Distribution Vehicles Based on Internet of Vehicles Platform

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Advanced Hybrid Information Processing (ADHIP 2023)

Abstract

In the phase of logistics distribution vehicle scheduling, the distribution time and travel distance of vehicles are relatively long due to the influence of the real-time change attribute characteristics of the actual traffic environment state. Therefore, this paper proposes an optimization scheduling algorithm for logistics distribution vehicles based on the Internet of Vehicles platform. The Internet of Vehicles platform including acquisition layer, transmission layer, data layer and application layer is constructed to achieve the acquisition and analysis of real-time information of the actual traffic environment status. In the logistics distribution vehicle scheduling phase, the objective function of comprehensively arranging the number of vehicles, the total distance traveled by the distribution vehicles and the time window constraint punishment is constructed. After the objective function is input into the Internet of Vehicles platform, the greedy algorithm strategy is used to achieve the optimal scheduling of vehicles. In the test results, the design algorithm achieves the goal of shortening the vehicle delivery time and driving distance without considering the results under traffic conditions and the scheduling effect under dynamic conditions. To sum up, the optimization scheduling algorithm of logistics distribution vehicles based on the Vehicle-to-everything platform can help optimize the travel distance and distribution time of vehicles, and improve the efficiency and accuracy of logistics distribution.

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References

  1. Zhao, Y., Chen, Z.H.: Shortest path optimization of reverse logistics vehicle based on local search. Comput. Simul. 39(11), 6 (2022)

    Google Scholar 

  2. Xu, X., Liu, L.: Research on distributed logistics scheduling method for workshop production based on hybrid particle swarm optimisation. Int. J. Manuf. Technol. Manage. 35(3), 234 (2021)

    Article  MathSciNet  Google Scholar 

  3. Pennetti, C.A., Jun, J., Jones, G.S., et al.: Temporal disaggregation of performance measures to manage uncertainty in transportation logistics and scheduling. ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A Civ. Eng. 7(1), 04020047 (2021)

    Article  Google Scholar 

  4. Ding, Z., Xu, X., Jiang, S., et al.: Emergency logistics scheduling with multiple supply-demand points based on grey interval. J. Saf. Sci. Resilience 3(2), 10 (2022)

    Google Scholar 

  5. Zhang, Y., Liu, J.: Emergency logistics scheduling under uncertain transportation time using online optimization methods. IEEE Access PP(99), 1 (2021)

    Google Scholar 

  6. Ding, Z., Zhao, Z., Liu, D., et al.: Multi-objective scheduling of relief logistics based on swarm intelligence algorithms and spatio-temporal traffic flow. J. Saf. Sci. Resilience 2(4), 8 (2021)

    Google Scholar 

  7. Lei, J., Hui, J., Ding, K., et al.: A framework for planning and scheduling shop floor logistics via cloud-edge collaboration. J. Phys. Conf. Ser. 1983(1), 012109 (2021)

    Article  Google Scholar 

  8. Midaoui, M.E., Qbadou, M., Mansouri, K.: Logistics chain optimization and scheduling of hospital pharmacy drugs using genetic algorithms: morocco case. Int. J. Web Based Learn. Teach. Technol. 2021(16), 54 (2021)

    Article  Google Scholar 

  9. Chen, T.: Decision-making support for transportation and logistics combining rough set fuzzy logic algorithm. J. Intell. Fuzzy Syst. Appl. Eng. Technol. 2021(4), 41 (2021)

    Google Scholar 

  10. Wang, S.: Artificial intelligence applications in the new model of logistics development based on wireless communication technology. Scientific Programming 2021(Pt.9), 2021 (2021)

    Google Scholar 

  11. Zhang, Q., Wang, T., Huang, K., et al.: Efficient dispatching system of railway vehicles based on internet of things technology. Pattern Recogn. Lett. 143(6), 14–18 (2021)

    Article  Google Scholar 

  12. Madahi, S.S.K., Nafisi, H., Abyaneh, H.A., et al.: Co-optimization of energy losses and transformer operating costs based on smart charging algorithm for plug-in electric vehicle parking lots. IEEE Trans. Transp. Electrification 7(2), 527–541 (2021)

    Article  Google Scholar 

  13. Li, C., Zhang, L., Zhang, L.: A route and speed optimization model to find conflict-free routes for automated guided vehicles in large warehouses based on quick response code technology. Adv. Eng. Inform. 52, 101604–101691 (2022)

    Article  Google Scholar 

  14. Masadeh, R.M.T., Alsharman, N., Sharieh, A.A., et al.: Task scheduling on cloud computing based on sea lion optimization algorithm. Int. J. Web Inf. Syst. 17(2), 99–116 (2021)

    Article  Google Scholar 

  15. Basu, M., Basu, S.: Horse herd optimization algorithm for fuel constrained day-ahead scheduling of isolated nanogrid. Appl. Artif. Intell. 35(15), 1250–1270 (2021)

    Article  Google Scholar 

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Acknowledgement

1. 2022 Dalian University of Science and Technology Higher Education Teaching Reform Research Project “Research and Practice on the Construction of Student Classroom Environment Based on the Internet of Things” (Project No. XJG202225).

2. This article is the phased research result of the 2022 "Integration of industry and education, school-enterprise cooperation" education reform and development project of the China Electronic Labor Association (Project No. Ciel 2022010).

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Correspondence to Zhuorong Li .

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Li, Z., Yao, Y., Zhang, H., Li, N., Sun, J. (2024). Optimization Scheduling Algorithm of Logistics Distribution Vehicles Based on Internet of Vehicles Platform. In: Yun, L., Han, J., Han, Y. (eds) Advanced Hybrid Information Processing. ADHIP 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 550. Springer, Cham. https://doi.org/10.1007/978-3-031-50552-2_5

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  • DOI: https://doi.org/10.1007/978-3-031-50552-2_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-50551-5

  • Online ISBN: 978-3-031-50552-2

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