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New integrated routing and surveillance model with drones and charging station considerations

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  • Zandieh, Fatemeh
  • Ghannadpour, Seyed Farid
  • Mazdeh, Mohammad Mahdavi

Abstract

Cash/valuables routing is vulnerable to attacks and robberies, so it is essential to prioritize transport security. This research employs a surveillance drone approach to enhance the transport security of cash/valuables routing. Using drones to identify suspicious and high-risk situations is a secure way to transport cash/valuables. Compared to ground-based operators, drones provide superior advantages such as improved security, efficiency, and accuracy. To this end, an integrated routing and surveillance problem is proposed to secure cash/valuables transport. In this problem, ground vehicles (GVs) and surveillance drones are routed in coordination. GVs are responsible for transporting and delivering cash/valuables, while drones are tasked with monitoring the GVs’ routes. The drone surveillance is as follows: before GVs leave the customers’ points, drones must surveil the GV through the link ahead and ensure their security. Links are surveilled in specific time windows. In this problem, charging stations are considered to swap drones’ batteries. In addition, an improved iterated local search (ILS) algorithm is designed in this study to optimize the proposed problem. The performance of the proposed algorithm is then evaluated in small and large sizes. Furthermore, a sensitivity analysis is performed on some key parameters to assess the proposed model. Finally, the proposed approach is implemented in a real-world case study in Iran, with the results analyzed.

Suggested Citation

  • Zandieh, Fatemeh & Ghannadpour, Seyed Farid & Mazdeh, Mohammad Mahdavi, 2024. "New integrated routing and surveillance model with drones and charging station considerations," European Journal of Operational Research, Elsevier, vol. 313(2), pages 527-547.
    • Handle: RePEc:eee:ejores:v:313:y:2024:i:2:p:527-547
    DOI: 10.1016/j.ejor.2023.08.035
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    References listed on IDEAS

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    1. Tikani, Hamid & Setak, Mostafa & Demir, Emrah, 2021. "A risk-constrained time-dependent cash-in-transit routing problem in multigraph under uncertainty," European Journal of Operational Research, Elsevier, vol. 293(2), pages 703-730.
    2. Soriano, Adria & Vidal, Thibaut & Gansterer, Margaretha & Doerner, Karl, 2020. "The vehicle routing problem with arrival time diversification on a multigraph," European Journal of Operational Research, Elsevier, vol. 286(2), pages 564-575.
    3. Talarico, Luca & Sörensen, Kenneth & Springael, Johan, 2015. "Metaheuristics for the risk-constrained cash-in-transit vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 244(2), pages 457-470.
    4. Hoogeboom, Maaike & Dullaert, Wout, 2019. "Vehicle routing with arrival time diversification," European Journal of Operational Research, Elsevier, vol. 275(1), pages 93-107.
    5. Sandra Ulrich Ngueveu & Christian Prins & Roberto Wolfler Calvo, 2013. "New Lower Bounds and Exact Method for the m -PVRP," Transportation Science, INFORMS, vol. 47(1), pages 38-52, February.
    6. Yan, Rui & Zhu, Xiaoping & Zhu, Xiaoning & Peng, Rui, 2023. "Joint optimisation of task abortions and routes of truck-and-drone systems under random attacks," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    7. Li, Hongqi & Chen, Jun & Wang, Feilong & Bai, Ming, 2021. "Ground-vehicle and unmanned-aerial-vehicle routing problems from two-echelon scheme perspective: A review," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1078-1095.
    8. Katharina Glock & Anne Meyer, 2020. "Mission Planning for Emergency Rapid Mapping with Drones," Transportation Science, INFORMS, vol. 54(2), pages 534-560, March.
    9. Kloster, Konstantin & Moeini, Mahdi & Vigo, Daniele & Wendt, Oliver, 2023. "The multiple traveling salesman problem in presence of drone- and robot-supported packet stations," European Journal of Operational Research, Elsevier, vol. 305(2), pages 630-643.
    10. Helena Ramalhinho Lourenço & Olivier C. Martin & Thomas Stützle, 2019. "Iterated Local Search: Framework and Applications," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, edition 3, chapter 0, pages 129-168, Springer.
    11. Cheng, Chun & Adulyasak, Yossiri & Rousseau, Louis-Martin, 2020. "Drone routing with energy function: Formulation and exact algorithm," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 364-387.
    12. Talarico, L. & Sörensen, K. & Springael, J., 2015. "The k-dissimilar vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 244(1), pages 129-140.
    13. Xia, Jun & Wang, Kai & Wang, Shuaian, 2019. "Drone scheduling to monitor vessels in emission control areas," Transportation Research Part B: Methodological, Elsevier, vol. 119(C), pages 174-196.
    14. Campbell, James F. & Corberán, Ángel & Plana, Isaac & Sanchis, José M. & Segura, Paula, 2021. "Solving the length constrained K-drones rural postman problem," European Journal of Operational Research, Elsevier, vol. 292(1), pages 60-72.
    15. Jeong, Ho Young & Song, Byung Duk & Lee, Seokcheon, 2019. "Truck-drone hybrid delivery routing: Payload-energy dependency and No-Fly zones," International Journal of Production Economics, Elsevier, vol. 214(C), pages 220-233.
    16. Rave, Alexander & Fontaine, Pirmin & Kuhn, Heinrich, 2023. "Drone location and vehicle fleet planning with trucks and aerial drones," European Journal of Operational Research, Elsevier, vol. 308(1), pages 113-130.
    17. Meng, Shanshan & Guo, Xiuping & Li, Dong & Liu, Guoquan, 2023. "The multi-visit drone routing problem for pickup and delivery services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    18. Allahyari, Somayeh & Yaghoubi, Saeed & Van Woensel, Tom, 2021. "A novel risk perspective on location-routing planning: An application in cash transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
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