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Logistics Network Distribution Optimization Based on Vehicle Sharing

Author

Listed:
  • Tao Yang

    (School of Continuing Education, Chongqing University of Education, Chongqing 400067, China)

  • Weixin Wang

    (Research Centre for International Business and Economics, School of International Business and Management, Sichuan International Studies University, Chongqing 400031, China)

Abstract

The development of the sharing economy has provided new ideas for a vehicle-sharing urban logistics network cooperative distribution strategy. In view of the lack of dispatching capacity or transportation capacity of logistics enterprises with multiple distribution centers, this paper proposes a vehicle-sharing urban logistics network cooperative distribution strategy. Based on the comprehensive consideration of a multi-distribution center, multi-model, rental vehicle, load, speed, fuel consumption, and other factors, the calculation method of vehicle energy consumption is introduced, the network collaborative distribution model with vehicle sharing is established, and an adaptive genetic algorithm combined with a scanning algorithm is designed. Finally, the validity and reliability of the mathematical model and algorithm are validated and analyzed by an example. The research results show that vehicle sharing can improve the efficiency of the distribution network and effectively reduce costs.

Suggested Citation

  • Tao Yang & Weixin Wang, 2022. "Logistics Network Distribution Optimization Based on Vehicle Sharing," Sustainability, MDPI, vol. 14(4), pages 1-12, February.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:2159-:d:748979
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    References listed on IDEAS

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    1. Renaud Masson & Anna Trentini & Fabien Lehuédé & Nicolas Malhéné & Olivier Péton & Houda Tlahig, 2017. "Optimization of a city logistics transportation system with mixed passengers and goods," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 81-109, March.
    2. Agatz, Niels A.H. & Erera, Alan L. & Savelsbergh, Martin W.P. & Wang, Xing, 2011. "Dynamic ride-sharing: A simulation study in metro Atlanta," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1450-1464.
    3. Tu, Wei & Fang, Zhixiang & Li, Qingquan & Shaw, Shih-Lung & Chen, BiYu, 2014. "A bi-level Voronoi diagram-based metaheuristic for a large-scale multi-depot vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 84-97.
    4. Baniasadi, Pouya & Foumani, Mehdi & Smith-Miles, Kate & Ejov, Vladimir, 2020. "A transformation technique for the clustered generalized traveling salesman problem with applications to logistics," European Journal of Operational Research, Elsevier, vol. 285(2), pages 444-457.
    5. Stiglic, Mitja & Agatz, Niels & Savelsbergh, Martin & Gradisar, Mirko, 2015. "The benefits of meeting points in ride-sharing systems," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 36-53.
    6. Furuhata, Masabumi & Dessouky, Maged & Ordóñez, Fernando & Brunet, Marc-Etienne & Wang, Xiaoqing & Koenig, Sven, 2013. "Ridesharing: The state-of-the-art and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 28-46.
    7. Agatz, Niels & Erera, Alan & Savelsbergh, Martin & Wang, Xing, 2012. "Optimization for dynamic ride-sharing: A review," European Journal of Operational Research, Elsevier, vol. 223(2), pages 295-303.
    8. Lee, Alan & Savelsbergh, Martin, 2015. "Dynamic ridesharing: Is there a role for dedicated drivers?," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 483-497.
    9. Stiglic, M. & Agatz, N.A.H. & Savelsbergh, M.W.P. & Gradisar, M., 2015. "The Benefits of Meeting Points in Ride-sharing Systems," ERIM Report Series Research in Management ERS-2015-003-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    10. Fatnassi, Ezzeddine & Chaouachi, Jouhaina & Klibi, Walid, 2015. "Planning and operating a shared goods and passengers on-demand rapid transit system for sustainable city-logistics," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 440-460.
    11. Arslan, A.M. & Agatz, N.A.H. & Kroon, L.G. & Zuidwijk, R.A., 2016. "Crowdsourced Delivery: A Dynamic Pickup and Delivery Problem with Ad-hoc Drivers," ERIM Report Series Research in Management ERS-2016-003-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    12. Archetti, Claudia & Savelsbergh, Martin & Speranza, M. Grazia, 2016. "The Vehicle Routing Problem with Occasional Drivers," European Journal of Operational Research, Elsevier, vol. 254(2), pages 472-480.
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    Cited by:

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    2. Zhao Zhang & Chun-Yan Xiao & Zhi-Guo Zhang, 2023. "Analysis and Empirical Study of Factors Influencing Urban Residents’ Acceptance of Routine Drone Deliveries," Sustainability, MDPI, vol. 15(18), pages 1-27, September.

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