Drone routing problem model for last-mile delivery using the public transportation capacity as moving charging stations

被引:0
|
作者
Amirhossein Moadab
Fatemeh Farajzadeh
Omid Fatahi Valilai
机构
[1] Washington State University,Department of Finance and Management Science, Carson College of Business
[2] Worcester Polytechnic Institute,Data Science
[3] Jacobs University Bremen,Department of Mathematics and Logistics
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
The fast and cost-efficient delivery of goods ordered online is logistically a challenging problem. Many firms are looking for ways to cut delivery times and costs by exploring opportunities to take advantage of drone technology. Deploying drones as a promising technology is more efficient from both environmental and economic perspectives in last-mile delivery. This paper considers a last-mile delivery system in which a set of drones are operated in coordination with public transportation system to deliver a set of orders to customer locations. A mathematical model based on Vehicle routing Problem (VRP) is extended to solve this problem. A real-world case inspired by Bremen 2025 transportation paradigm is also developed to validate the developed mathematical formulation. Results show that the sequence of visiting customers and public transport stations highly impacts the remaining charge and efficiency of drone tour planning. Also, using public transport vehicles, which enables drones to charge their battery or to approach customers, can reduce the number of drones required for satisfying the demands in a service area. The results show that there are high potentials to save energy for drone-enabled last-mile delivery by using the public transportation network.
引用
收藏
相关论文
共 45 条
  • [21] Using public transport in a 2-echelon last-mile delivery network
    Schmidt, Jeanette
    Tilk, Christian
    Irnich, Stefan
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2024, 317 (03) : 827 - 840
  • [22] Identifying the Optimal Packing and Routing to Improve Last-Mile Delivery Using Cargo Bicycles
    Naumov, Vitalii
    Pawlus, Michal
    [J]. ENERGIES, 2021, 14 (14)
  • [23] A last-mile drone-assisted one-to-one pickup and delivery problem with multi-visit drone trips
    Luo, Zhihao
    Gu, Ruixue
    Poon, Mark
    Liu, Zhong
    Lim, Andrew
    [J]. COMPUTERS & OPERATIONS RESEARCH, 2022, 148
  • [24] Selecting Freight Transportation Modes in Last-Mile Urban Distribution in Pamplona (Spain): An Option for Drone Delivery in Smart Cities
    Serrano-Hernandez, Adrian
    Ballano, Aitor
    Faulin, Javier
    [J]. ENERGIES, 2021, 14 (16)
  • [25] Last mile delivery routing problem using autonomous electric vehicles
    Moradi, Nima
    Sadati, Ihsan
    Catay, Buelent
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2023, 184
  • [26] Optimised solutions to the last-mile delivery problem in London using a combination of walking and driving
    Martinez-Sykora, Antonio
    McLeod, Fraser
    Lamas-Fernandez, Carlos
    Bektas, Tolga
    Cherrett, Tom
    Allen, Julian
    [J]. ANNALS OF OPERATIONS RESEARCH, 2020, 295 (02) : 645 - 693
  • [27] Optimised solutions to the last-mile delivery problem in London using a combination of walking and driving
    Antonio Martinez-Sykora
    Fraser McLeod
    Carlos Lamas-Fernandez
    Tolga Bektaş
    Tom Cherrett
    Julian Allen
    [J]. Annals of Operations Research, 2020, 295 : 645 - 693
  • [28] Reconfiguration of last-mile supply chain for parcel delivery using machine learning and routing optimization
    Ramirez-Villamil, Angie
    Montoya-Torres, Jairo R.
    Jaegler, Anicia
    Cuevas-Torres, Juan M.
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2023, 184
  • [29] Optimizing last-mile delivery services: a robust truck-drone cooperation model and hybrid metaheuristic algorithm
    Mirzapour Al-e-Hashem, Seyed Mohammad Javad
    Hejazi, Taha-Hossein
    Haghverdizadeh, Ghazal
    Shidpour, Mohsen
    [J]. ANNALS OF OPERATIONS RESEARCH, 2024,
  • [30] A-VRPD: Automating Drone-Based Last-Mile Delivery Using Self-Driving Cars
    Imran, Navid Mohammad
    Mishra, Sabyasachee
    Won, Myounggyu
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (09) : 9599 - 9612