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Mathematical Investigation on the Sustainability of UAV Logistics

Author

Listed:
  • Joonyup Eun

    (Graduate School of Management of Technology, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea)

  • Byung Duk Song

    (Department of Industrial and Management Systems Engineering, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si, Gyeonggi-do 17104, Korea)

  • Sangbok Lee

    (Department of Industrial and Management Engineering, Hansung University, 116 Samsungyoro16-gil, Seongbuk-gu, Seoul 02876, Korea)

  • Dae-Eun Lim

    (Department of Industrial Engineering, Kangwon National University, 1 Kangwondaehak-gil, Gangwon-do 24341, Korea)

Abstract

Unmanned aerial vehicles (UAVs) are expected to make groundbreaking changes in the logistics industry. Leading logistics companies have been developing and testing their usage of UAVs recently as an environmentally friendly and cost-effective option. In this paper, we investigate how much the UAV delivery service is environmentally friendly compared to the traditional ground vehicle (GV) delivery service. Since there are fuel (battery) and loadable weight restrictions in the UAV delivery, multi-hopping of UAV is necessary, which may cause a large consumption of electrical energy. We present a two-phase approach. In Phase I, a new vehicle routing model to obtain optimal delivery schedules for both UAV-alone and GV-alone delivery systems is proposed, which considers each system’s restrictions, such as the max loadable weight and fuel replenishment. In Phase II, CO 2 emissions are computed as a sustainability measure based on the travelling distance of the optimal route obtained from Phase I, along with various GV travel-speeds. A case study finds that the UAV-alone delivery system is much more CO 2 efficient in all ranges of the GV speeds investigated.

Suggested Citation

  • Joonyup Eun & Byung Duk Song & Sangbok Lee & Dae-Eun Lim, 2019. "Mathematical Investigation on the Sustainability of UAV Logistics," Sustainability, MDPI, vol. 11(21), pages 1-15, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:21:p:5932-:d:280124
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    References listed on IDEAS

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    Cited by:

    1. Bo Peng & Lifan Wu & Yuxin Yi & Xiding Chen, 2020. "Solving the Multi-Depot Green Vehicle Routing Problem by a Hybrid Evolutionary Algorithm," Sustainability, MDPI, vol. 12(5), pages 1-19, March.
    2. Nils Boysen & Stefan Fedtke & Stefan Schwerdfeger, 2021. "Last-mile delivery concepts: a survey from an operational research perspective," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 1-58, March.
    3. Michael Dienstknecht & Nils Boysen & Dirk Briskorn, 2022. "The traveling salesman problem with drone resupply," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1045-1086, December.
    4. Boris V. Rumiantsev & Rasul A. Kochkarov & Azret A. Kochkarov, 2023. "Graph-Clustering Method for Construction of the Optimal Movement Trajectory under the Terrain Patrolling," Mathematics, MDPI, vol. 11(1), pages 1-13, January.
    5. Kaiping Wang & Mingzhu Song & Meng Li, 2021. "Cooperative Multi-UAV Conflict Avoidance Planning in a Complex Urban Environment," Sustainability, MDPI, vol. 13(12), pages 1-21, June.
    6. Young Dae Ko & Byung Duk Song, 2021. "Complementary Cooperation of CCTV and UAV Systems for Tourism Security and Sustainability," Sustainability, MDPI, vol. 13(19), pages 1-15, September.
    7. Yi Li & Min Liu & Dandan Jiang, 2022. "Application of Unmanned Aerial Vehicles in Logistics: A Literature Review," Sustainability, MDPI, vol. 14(21), pages 1-18, November.
    8. Jianxun Li & Hao Liu & Kin Keung Lai & Bhagwat Ram, 2022. "Vehicle and UAV Collaborative Delivery Path Optimization Model," Mathematics, MDPI, vol. 10(20), pages 1-22, October.

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