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Multi-Criteria Simulation-Optimization Analysis of Usage of Automated Parcel Lockers: A Practical Approach

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  • Bartosz Sawik

    (Department of Business Informatics and Engineering Management, AGH University of Science and Technology, 30-059 Krakow, Poland
    Department of Statistics, Computer Science and Mathematics, Public University of Navarre, 31006 Pamplona, Spain
    Haas School of Business, University of California at Berkeley, Berkeley, CA 94720, USA)

  • Adrian Serrano-Hernandez

    (Institute of Smart Cities, Department of Statistics, Computer Science and Mathematics, Public University of Navarre, 31006 Pamplona, Spain)

  • Alvaro Muro

    (Department of Statistics, Computer Science and Mathematics, Public University of Navarre, 31006 Pamplona, Spain)

  • Javier Faulin

    (Institute of Smart Cities, Department of Statistics, Computer Science and Mathematics, Public University of Navarre, 31006 Pamplona, Spain)

Abstract

The rapid growth of electronic commerce is having an impact on the way urban logistics are organized. In metropolitan settings, the last-mile delivery problem, i.e., the problem regarding the final stage of delivering a shipment to a consumer, is a major concern due to its inefficiency. The development of a convenient automated parcel lockers (APLs) network improves last-mile distribution by reducing the number of vehicles, the distances driven, and the number of delivery stops. Using automated parcel lockers, the last-mile issue could be overcome for the environment’s benefit. This study aimed to define and validate an APL network containing hundreds of APLs with the use of an example made up of real case study data from the city of Poznań in Poland. The goal of this research was to use mathematical programming for optimization and simulation to tackle the facility location problem for automated parcel lockers through a practical approach. Multi-criteria simulation-optimization analysis was used to assess the data. In fact, the simulation was carried out using Anylogic software and the optimization with the use of the Java programming language and CPLEX solver. Three years were simulated, allowing for comparable results for each year in terms of expenses, e-shoppers, APL users, and demand evolution, as well as achieving the city’s optimal locker usage. Finally, encouraging conclusions were obtained, such as the relationship between the demand and the number of lockers, along with the model’s limitations.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:23:p:4423-:d:982490
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    References listed on IDEAS

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    1. Bartosz Sawik, 2012. "Downside Risk Approach for Multi-Objective Portfolio Optimization," Operations Research Proceedings, in: Diethard Klatte & Hans-Jakob Lüthi & Karl Schmedders (ed.), Operations Research Proceedings 2011, edition 127, pages 191-196, Springer.
    2. Chen, Ching-Fu & White, Christopher & Hsieh, Yi-En, 2020. "The role of consumer participation readiness in automated parcel station usage intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    3. Tsai, Yao-Te & Tiwasing, Praewwanit, 2021. "Customers’ intention to adopt smart lockers in last-mile delivery service: A multi-theory perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    4. Vakulenko, Yulia & Hellström, Daniel & Hjort, Klas, 2018. "What's in the parcel locker? Exploring customer value in e-commerce last mile delivery," Journal of Business Research, Elsevier, vol. 88(C), pages 421-427.
    5. Yael Deutsch & Boaz Golany, 2018. "A parcel locker network as a solution to the logistics last mile problem," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 251-261, January.
    6. Yuen, Kum Fai & Wang, Xueqin & Ng, Li Ting Wendy & Wong, Yiik Diew, 2018. "An investigation of customers’ intention to use self-collection services for last-mile delivery," Transport Policy, Elsevier, vol. 66(C), pages 1-8.
    7. 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.
    8. Buldeo Rai, Heleen & Verlinde, Sara & Macharis, Cathy, 2021. "Unlocking the failed delivery problem? Opportunities and challenges for smart locks from a consumer perspective," Research in Transportation Economics, Elsevier, vol. 87(C).
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    Cited by:

    1. Alves, Roberta & Pereira, Cecília Aparecida & Lima, Renato da Silva, 2023. "Operational cost analysis for e-commerce deliveries using agent-based modeling and simulation," Research in Transportation Economics, Elsevier, vol. 101(C).
    2. Bartosz Sawik, 2023. "Space Mission Risk, Sustainability and Supply Chain: Review, Multi-Objective Optimization Model and Practical Approach," Sustainability, MDPI, vol. 15(14), pages 1-25, July.

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