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The multiple traveling salesman problem in presence of drone- and robot-supported packet stations

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  • Kloster, Konstantin
  • Moeini, Mahdi
  • Vigo, Daniele
  • Wendt, Oliver

Abstract

In this paper, we introduce the multiple Traveling Salesman Problem with Drone Stations (mTSP-DS), which is an extension to the classical multiple Traveling Salesman Problem (mTSP). In the mTSP-DS, we have a depot, a set of trucks, and some packet stations that host a given number of autonomous vehicles (drones or robots). The trucks start their mission from the depot and can supply some packet stations, which can then launch and operate drones/robots to serve customers. The goal is to serve all customers either by truck or by drones/robots while minimizing the makespan. We formulate the mTSP-DS as a mixed integer linear programming (MILP) model to solve small instances. To address larger instances, we first introduce two variants of a decomposition-based matheuristic. Afterwards, we suggest a third approach that is based on populating a solution pool with several restarts of an iterated local search metaheuristic, which is followed by determining the best combination of tours using a set-partitioning model. To verify the performance of our algorithms, we conducted extensive computational experiments. According to the numerical results, we observe that the use of drone stations leads to considerable savings in delivery time compared to traditional mTSP solutions. Furthermore, we investigated the energy consumption of trucks and drones. Indeed, depending on the energy consumption coefficients of trucks and drones as well as on the distance covered by drones, the mTSP-DS can also achieve energy savings in comparison to mTSP solutions.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:305:y:2023:i:2:p:630-643
    DOI: 10.1016/j.ejor.2022.06.004
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Mengyuan Gou & Haiyan Yu, 2023. "Online Delivery Problem for Hybrid Truck–Drone System with Independent and Truck-Carried Drones," Sustainability, MDPI, vol. 15(2), pages 1-15, January.
    2. Yin, Yunqiang & Li, Dongwei & Wang, Dujuan & Ignatius, Joshua & Cheng, T.C.E. & Wang, Sutong, 2023. "A branch-and-price-and-cut algorithm for the truck-based drone delivery routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1125-1144.
    3. Yin, Yunqiang & Yang, Yongjian & Yu, Yugang & Wang, Dujuan & Cheng, T.C.E., 2023. "Robust vehicle routing with drones under uncertain demands and truck travel times in humanitarian logistics," Transportation Research Part B: Methodological, Elsevier, vol. 174(C).
    4. Song Liu & Xinhua Gao & Liu Chen & Sihui Zhou & Yong Peng & Dennis Z. Yu & Xianting Ma & Yan Wang, 2023. "Multi-Traveler Salesman Problem for Unmanned Vehicles: Optimization through Improved Hopfield Neural Network," Sustainability, MDPI, vol. 15(20), pages 1-25, October.

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