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Multiobjective Optimization for Planning the Service Areas of Smart Parcel Locker Facilities in Logistics Last Mile Delivery

Author

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  • Zhen-Hua Che

    (Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 106, Taiwan)

  • Tzu-An Chiang

    (Department of Business Administration, National Taipei University of Business, Taipei 100, Taiwan)

  • Yun-Jhen Luo

    (Manufacturing Department, Taiwan Semiconductor Manufacturing Company, Taichung 407, Taiwan)

Abstract

The planning of the location service areas of smart parcel locker facilities became a critical aspect of logistics last mile delivery. In e-commerce, the efficiency of delivering merchandise from retailer warehouses to customers determines the competitiveness of retailers and delivery operators. The considerable increases in e-commerce transactions and safety concerns under the COVID-19 (Coronavirus disease 2019) pandemic made home delivery services even more inefficient than before, which resulted in the considerable increase in social costs. In numerous countries, smart parcel lockers were adopted to increase delivery efficiency, decrease the risk of COVID-19 infection, and reduce the burden on society. This study proposed a multiobjective optimization mathematical model for investigating the planning of the location service areas of smart parcel locker facilities, and then the optimization mathematical model was solved using a combination of the Taguchi method (TA) and nondominant sorting genetic algorithm II (NSGA-II). Finally, this composite approach was applied to a case study in producing favorable solutions for facility location service area planning.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:3:p:422-:d:737050
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    References listed on IDEAS

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    2. Roel Gevaers & Eddy Van de Voorde & Thierry Vanelslander, 2011. "Characteristics and Typology of Last-mile Logistics from an Innovation Perspective in an Urban Context," Chapters, in: Cathy Macharis & Sandra Melo (ed.), City Distribution and Urban Freight Transport, chapter 3, Edward Elgar Publishing.
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    Cited by:

    1. 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.
    2. Wang, Yang & Bi, Mengyu & Lai, Jianhui & Wang, Chenxi & Chen, Yanyan & Holguín-Veras, José, 2024. "Recourse strategy for the routing problem of mobile parcel lockers with time windows under uncertain demands," European Journal of Operational Research, Elsevier, vol. 316(3), pages 942-957.
    3. 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.
    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. 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.
    6. 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.
    7. 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.

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