Sustainable Operations of Last Mile Logistics Based on Machine Learning Processes

被引:2
|
作者
Orsic, Jerko [1 ]
Jereb, Borut [2 ]
Obrecht, Matevz [2 ]
机构
[1] Epilog Doo, Ljubljana 1000, Slovenia
[2] Univ Maribor, Fac Logist, Celje 3000, Slovenia
关键词
supply chain management; real-time; home delivery; business modeling; e-commerce; time window;
D O I
10.3390/pr10122524
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The last-mile logistics is regarded as one of the least efficient, most expensive, and polluting part of the entire supply chain and has a significant impact and consequences on sustainable delivery operations. The leading business model in e-commerce called Attended Home Delivery is the most expensive and demanding when a short delivery window is mutually agreed upon with the customer, decreasing possible optimizing flexibility. On the other hand, last-mile logistics is changing as decisions should be made in real time. This paper is focused on the proposed solution of sustainability opportunities in Attended Home Delivery, where we use a new approach to achieve more sustainable deliveries with machine learning forecasts based on real-time data, different dynamic route planning algorithms, tracking logistics events, fleet capacities and other relevant data. The developed model proposes to influence customers to choose a more sustainable delivery time window with important sustainability benefits based on machine learning to predict accurate time windows with real-time data influence. At the same time, better utilization of vehicles, less congestion, and fewer failures at home delivery are achieved. More sustainable routes are selected in the preplanning process due to predicted traffic or other circumstances. Increasing time slots from 2 to 4 h makes it possible to improve travel distance by about 5.5% and decrease cost by 11% if we assume that only 20% of customers agree to larger time slots.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] Optimization and Machine Learning Applied to Last-Mile Logistics: A Review
    Giuffrida, Nadia
    Fajardo-Calderin, Jenny
    Masegosa, Antonio D.
    Werner, Frank
    Steudter, Margarete
    Pilla, Francesco
    SUSTAINABILITY, 2022, 14 (09)
  • [2] A Concept for a Consumer-Centered Sustainable Last Mile Logistics
    Freitag, Michael
    Kotzab, Herbert
    DYNAMICS IN LOGISTICS (LDIC 2020), 2020, : 196 - 203
  • [3] Evaluation of a Sustainable Crowd Logistics Concept for the Last Mile Based on Electric Cargo Bikes
    Schulte, Richard
    Leibenath, Mattes
    Woeltjen, Lars
    Kuehne, Uta
    vom Berg, Benjamin Wagner
    ADVANCES AND NEW TRENDS IN ENVIRONMENTAL INFORMATICS: A BOGEYMAN OR SAVIOUR FOR THE UN SUSTAINABILITY GOALS?, 2022, : 199 - 216
  • [4] SOLFI: An Integrated Platform for Sustainable Urban Last-Mile Logistics' Operations-Study, Design and Development
    Teixeira, Leonor
    Ramos, Ana Luisa
    Costa, Carolina
    Pedrosa, Dulce
    Faria, Cesar
    Pimentel, Carina
    SUSTAINABILITY, 2023, 15 (03)
  • [5] A machine learning optimization approach for last-mile delivery and third-party logistics
    Bruni, Maria Elena
    Fadda, Edoardo
    Fedorov, Stanislav
    Perboli, Guido
    COMPUTERS & OPERATIONS RESEARCH, 2023, 157
  • [6] Transforming Last-Mile Logistics: Opportunities for more Sustainable Deliveries
    Bates, Oliver
    Friday, Adrian
    Allen, Julian
    Cherrett, Tom
    Mcleod, Fraser
    Bektas, Tolga
    ThuBa Nguyen
    Piecyk, Maja
    Piotrowska, Marzena
    Wise, Sarah
    Davies, Nigel
    PROCEEDINGS OF THE 2018 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI 2018), 2018,
  • [7] Sustainable Urban Last-Mile Logistics: A Systematic Literature Review
    Silva, Vasco
    Amaral, Antonio
    Fontes, Tania
    SUSTAINABILITY, 2023, 15 (03)
  • [8] Sustainable last mile logistics employing drones and e-bikes
    Santiago-Montano, Stephanie
    Silva, Daniel F.
    Smith, Alice E.
    INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION, 2024, 18 (10) : 887 - 902
  • [9] Data Science To Measure The Efficiency Of Delivery Of The Last Mile Processes In Logistics
    Saavedra Gastelum, Veronica
    Gonzalez Almaguer, Carlos Alberto
    Murrieta Cortes, Beatriz
    Aviles Rabanales, Erendira Gabriela
    PROCEEDINGS OF THE CONFERENCE ON PRODUCTION SYSTEMS AND LOGISTICS, CPSL 2023-1, 2023, : 742 - 748
  • [10] New City Logistics Paradigm: From the "Last Mile" to the "Last 50 Miles" Sustainable Distribution
    Faccio, Maurizio
    Gamberi, Mauro
    SUSTAINABILITY, 2015, 7 (11) : 14873 - 14894