IDEAS home Printed from https://ideas.repec.org/a/gam/jlogis/v8y2024i2p61-d1415333.html
   My bibliography  Save this article

Performance Analysis of Automated Parcel Lockers in Urban Delivery: Combined Agent-Based–Monte Carlo Simulation Approach

Author

Listed:
  • Eugen Rosca

    (Transport, Traffic and Logistics Department, National University of Science and Technology Politehnica Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania)

  • Florin Rusca

    (Transport, Traffic and Logistics Department, National University of Science and Technology Politehnica Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania)

  • Mircea Augustin Rosca

    (Transport, Traffic and Logistics Department, National University of Science and Technology Politehnica Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania)

  • Aura Rusca

    (Transport, Traffic and Logistics Department, National University of Science and Technology Politehnica Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania)

Abstract

Background : The habitat structure, the environmental impact, the market acceptance, the changes in consumers’ preferences, and the pandemic urged for innovative solutions in urban last-mile delivery. Parcel lockers are among the most preferred solutions by customers due to their home proximity, time availability, and cost efficiency. Methods : This paper introduces an agent-based model (ABM) and a Monte Carlo simulation program to analyze in detail the activity of parcel locker points. The ABM describes the behavior of the agents (customers, parcels, lockers, delivery agents). The simulation is realized using ARENA 12 software. Two scenarios are created based on the number of daily delivery shifts; for each scenario, 300 simulation experiments with various input data are conducted. Results : Three measures of performance (MOPs) are selected to assess the system activity: the number of daily delivered parcels, the delivery time of an order, and the daily delayed orders. The simulation outputs reveal significant predictors of MOPs and disclose moments when actions need to be taken to increase system capacity or change customer behavior. Conclusions : The versatility of the simulation model in terms of input variables makes it a useful decision support tool for planning by highlighting quantitative assessments, organizing delivery activity, along with influences due to customer behavior changes.

Suggested Citation

  • Eugen Rosca & Florin Rusca & Mircea Augustin Rosca & Aura Rusca, 2024. "Performance Analysis of Automated Parcel Lockers in Urban Delivery: Combined Agent-Based–Monte Carlo Simulation Approach," Logistics, MDPI, vol. 8(2), pages 1-26, June.
  • Handle: RePEc:gam:jlogis:v:8:y:2024:i:2:p:61-:d:1415333
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2305-6290/8/2/61/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2305-6290/8/2/61/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhen-Hua Che & Tzu-An Chiang & Yun-Jhen Luo, 2022. "Multiobjective Optimization for Planning the Service Areas of Smart Parcel Locker Facilities in Logistics Last Mile Delivery," Mathematics, MDPI, vol. 10(3), pages 1-22, January.
    2. Russo, Francesco & Comi, Antonio, 2011. "A model system for the ex-ante assessment of city logistics measures," Research in Transportation Economics, Elsevier, vol. 31(1), pages 81-87.
    3. Bartosz Sawik & Adrian Serrano-Hernandez & Alvaro Muro & Javier Faulin, 2022. "Multi-Criteria Simulation-Optimization Analysis of Usage of Automated Parcel Lockers: A Practical Approach," Mathematics, MDPI, vol. 10(23), pages 1-17, November.
    4. Ivan Cardenas & Yari Borbon-Galvez & Thomas Verlinden & Eddy Van de Voorde & Thierry Vanelslander & Wouter Dewulf, 2017. "City logistics, urban goods distribution and last mile delivery and collection," Competition and Regulation in Network Industries, , vol. 18(1-2), pages 22-43, March.
    5. Schwerdfeger, Stefan & Boysen, Nils, 2020. "Optimizing the changing locations of mobile parcel lockers in last-mile distribution," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1077-1094.
    6. Massimo Di Gangi & Antonio Polimeni & Orlando Marco Belcore, 2023. "Freight Distribution in Small Islands: Integration between Naval Services and Parcel Lockers," Sustainability, MDPI, vol. 15(9), pages 1-15, May.
    7. Shichang Pan & Lele Zhang & Russell G. Thompson & Hadi Ghaderi, 2021. "A parcel network flow approach for joint delivery networks using parcel lockers," International Journal of Production Research, Taylor & Francis Journals, vol. 59(7), pages 2090-2115, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Massimo Di Gangi & Antonio Polimeni & Orlando Marco Belcore, 2023. "Freight Distribution in Small Islands: Integration between Naval Services and Parcel Lockers," Sustainability, MDPI, vol. 15(9), pages 1-15, May.
    2. Leise Kelli de Oliveira & Isabela Kopperschmidt de Oliveira & João Guilherme da Costa Braga França & Gustavo Wagner Nunes Balieiro & Jean Francisco Cardoso & Tiago Bogo & Diego Bogo & Marco Adriano Li, 2022. "Integrating Freight and Public Transport Terminals Infrastructure by Locating Lockers: Analysing a Feasible Solution for a Medium-Sized Brazilian Cities," Sustainability, MDPI, vol. 14(17), pages 1-16, August.
    3. Sergio Maria Patella & Gianluca Grazieschi & Valerio Gatta & Edoardo Marcucci & Stefano Carrese, 2020. "The Adoption of Green Vehicles in Last Mile Logistics: A Systematic Review," Sustainability, MDPI, vol. 13(1), pages 1-29, December.
    4. Kahr, Michael, 2022. "Determining locations and layouts for parcel lockers to support supply chain viability at the last mile," Omega, Elsevier, vol. 113(C).
    5. Rafael Villa & Andrés Monzón, 2021. "Mobility Restrictions and E-Commerce: Holistic Balance in Madrid Centre during COVID-19 Lockdown," Economies, MDPI, vol. 9(2), pages 1-19, April.
    6. Lin, Yun Hui & Wang, Yuan & He, Dongdong & Lee, Loo Hay, 2020. "Last-mile delivery: Optimal locker location under multinomial logit choice model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    7. Bartosz Sawik, 2024. "Optimizing Last-Mile Delivery: A Multi-Criteria Approach with Automated Smart Lockers, Capillary Distribution and Crowdshipping," Logistics, MDPI, vol. 8(2), pages 1-30, May.
    8. Liu, Yubin & Ye, Qiming & Escribano-Macias, Jose & Feng, Yuxiang & Candela, Eduardo & Angeloudis, Panagiotis, 2023. "Route planning for last-mile deliveries using mobile parcel lockers: A hybrid q-learning network approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    9. Van Asch, Thomas & Dewulf, Wouter & Kupfer, Franziska & Cárdenas, Ivan & Van de Voorde, Eddy, 2020. "Cross-border e-commerce logistics – Strategic success factors for airports," Research in Transportation Economics, Elsevier, vol. 79(C).
    10. Daniel Kaszubowski, 2019. "A Method for the Evaluation of Urban Freight Transport Models as a Tool for Improving the Delivery of Sustainable Urban Transport Policy," Sustainability, MDPI, vol. 11(6), pages 1-23, March.
    11. Vijoleta Vrhovac & Stana Vasić & Stevan Milisavljević & Branislav Dudić & Peter Štarchoň & Marina Žižakov, 2023. "Measuring E-Commerce User Experience in the Last-Mile Delivery," Mathematics, MDPI, vol. 11(6), pages 1-21, March.
    12. Gleb V. Savin, 2021. "The smart city transport and logistics system: Theory, methodology and practice," Upravlenets, Ural State University of Economics, vol. 12(6), pages 67-86, October.
    13. Leung, Abraham & Lachapelle, Ugo & Burke, Matthew, 2023. "Spatio-temporal analysis of Australia Post parcel locker use during the initial system growth phase in Queensland (2013–2017)," Journal of Transport Geography, Elsevier, vol. 110(C).
    14. Snežana Tadić & Mladen Krstić & Željko Stević & Miloš Veljović, 2023. "Locating Collection and Delivery Points Using the p -Median Location Problem," Logistics, MDPI, vol. 7(1), pages 1-17, February.
    15. Marisdea Castiglione & Antonio Comi & Rosita De Vincentis & Andreea Dumitru & Marialisa Nigro, 2022. "Delivering in Urban Areas: A Probabilistic-Behavioral Approach for Forecasting the Use of Electric Micromobility," Sustainability, MDPI, vol. 14(15), pages 1-13, July.
    16. Taufiq Suryo Nugroho & Chandra Balijepalli & Anthony Whiteing, 2021. "Independent Retailer Restocking Choices in Urban Goods Movement and Interaction Effects with Traditional Markets," Networks and Spatial Economics, Springer, vol. 21(4), pages 933-969, December.
    17. Fabusuyi, Tayo & Twumasi-Boakye, Richard & Broaddus, Andrea & Fishelson, James & Hampshire, Robert Cornelius, 2020. "Estimating small area demand for online package delivery," Journal of Transport Geography, Elsevier, vol. 88(C).
    18. Anna Corinna Cagliano & Alberto Marco & Giulio Mangano & Giovanni Zenezini, 2017. "Levers of logistics service providers’ efficiency in urban distribution," Operations Management Research, Springer, vol. 10(3), pages 104-117, December.
    19. Dukkanci, Okan & Campbell, James F. & Kara, Bahar Y., 2024. "Facility location decisions for drone delivery: A literature review," European Journal of Operational Research, Elsevier, vol. 316(2), pages 397-418.
    20. Agnieszka Szmelter-Jarosz & Jagienka Rześny-Cieplińska, 2019. "Priorities of Urban Transport System Stakeholders According to Crowd Logistics Solutions in City Areas. A Sustainability Perspective," Sustainability, MDPI, vol. 12(1), pages 1-19, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlogis:v:8:y:2024:i:2:p:61-:d:1415333. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.