The sustainable hybrid truck-drone delivery model with stochastic customer existence

被引:7
|
作者
Teimoury, Ebrahim [1 ]
Rashid, Reza [1 ]
机构
[1] Iran Univ Sci & Technol, Dept Ind Engn, Tehran 16844, Iran
关键词
Last -mile delivery; Coordinating truck and drone; Branch-and-Bound algorithm; Markov chain; Stochastic customer presence; Sustainable routing; VEHICLE-ROUTING PROBLEM; TRAVELING SALESMAN PROBLEM; OPTIMIZATION; ALGORITHM;
D O I
10.1016/j.retrec.2023.101325
中图分类号
F [经济];
学科分类号
02 ;
摘要
Drone delivery is a fast delivery mode that has gained tremendous attention from academia and various companies in recent years. However, due to limited battery and payload capacities which may reduce the system's efficiency, it is better to coordinate ground vehicles and drones to take advantage of both trucks' large capacity and the drone's high speed. As a restriction for realistic parcel delivery systems, customer presence is only sometimes deterministic. For instance, a customer makes an order from an e-retailer, but due to various probable reasons, he cannot be present at home to get service. In this paper, we have introduced a sustainable hybrid truck-drone delivery model with stochastic customer presence. We have modeled the system with the Markov chain and proposed a linear mathematical model. This work processes with a heuristic and a Branch-and-Bound algorithm. Also, we have carried out numerous computational experiments to evaluate the proposed solution methods' performance, where the results show the efficiency of the proposed algorithms. Finally, we performed a detailed sensitivity analysis on a case study and studied various aspects of the problem. The results highlight that truck and drone coordination reduces completion time, operational costs, truck emissions, and social penalties.
引用
收藏
页数:17
相关论文
共 50 条
  • [21] Research on truck-drone collaborative route planning for rural logistics delivery services
    Wang, Yong
    Yang, Suo
    Wang, Xi Vincent
    Wang, Lihui
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [22] En route truck-drone parcel delivery for optimal vehicle routing strategies
    Marinelli, Mario
    Caggiani, Leonardo
    Ottomanelli, Michele
    Dell'Orco, Mauro
    IET INTELLIGENT TRANSPORT SYSTEMS, 2018, 12 (04) : 253 - 261
  • [23] Cooperative Truck-Drone Delivery Path Optimization under Urban Traffic Restriction
    Weng, Ying-Ying
    Wu, Rong-Yu
    Zheng, Yu-Jun
    DRONES, 2023, 7 (01)
  • [24] Truck-Drone Delivery Optimization Based on Multi-Agent Reinforcement Learning
    Bi, Zhiliang
    Guo, Xiwang
    Wang, Jiacun
    Qin, Shujin
    Liu, Guanjun
    DRONES, 2024, 8 (01)
  • [25] How the Wind Can Be Leveraged for Saving Energy in a Truck-Drone Delivery System
    Sorbelli, Francesco Betti
    Coro, Federico
    Palazzetti, Lorenzo
    Pinotti, Cristina M.
    Rigoni, Giulio
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (04) : 4038 - 4049
  • [26] A new truck-drone routing problem for parcel delivery by considering energy consumption and altitude
    Momeni, Maryam
    Al-e-Hashem, S. M. J. Mirzapour
    Heidari, Ali
    ANNALS OF OPERATIONS RESEARCH, 2024, 337 (SUPPL 1) : 25 - 25
  • [27] The truck-drone routing optimization problem: mathematical model and a VNS approach
    Ndiaye, Malick
    Osman, Ahmed
    Salhi, Said
    Madani, Batool
    OPTIMIZATION LETTERS, 2024, 18 (04) : 1023 - 1052
  • [28] A hybrid variable neighborhood search heuristic for the sustainable time-dependent truck-drone routing problem with rendezvous locations
    Teimoury, Ebrahim
    Rashid, Reza
    JOURNAL OF HEURISTICS, 2024, 30 (1-2) : 1 - 41
  • [29] A hybrid variable neighborhood search heuristic for the sustainable time-dependent truck-drone routing problem with rendezvous locations
    Ebrahim Teimoury
    Reza Rashid
    Journal of Heuristics, 2024, 30 : 1 - 41
  • [30] A hybrid multi-objective solution approach for a reliable truck-drone routing problem integrated with pickup and delivery services
    Khalaj Rahimi, Sanaz
    Rahmani, Donya
    TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH, 2025, 17 (02): : 230 - 248