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Smart logistics: distributed control of green crowdsourced parcel services

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  • Seokgi Lee
  • Yuncheol Kang
  • Vittaldas V. Prabhu

Abstract

This paper presents the development of an integrated decision-making framework for on-demand parcel delivery services that considers Just-In-Time delivery, fuel consumption and carbon emissions. Optimal policies based on the Markov decision process are established to allow for inclusion of parcel delivery requests. The framework’s integrated dynamic algorithm, based on a continuous variable feedback control, allows for unified processing of delivery requests and route scheduling. Computational experiments show that the integrated approach could increase revenue by 6.4% by reducing fuel and emission costs by 2.5%; however, the approach may incur more cost in terms of timeliness compared to a myopic approach.

Suggested Citation

  • Seokgi Lee & Yuncheol Kang & Vittaldas V. Prabhu, 2016. "Smart logistics: distributed control of green crowdsourced parcel services," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 6956-6968, December.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:23:p:6956-6968
    DOI: 10.1080/00207543.2015.1132856
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    Cited by:

    1. Weihua Liu & Shangsong Long & Yanjie Liang & Jinkun Wang & Shuang Wei, 2023. "The influence of leadership and smart level on the strategy choice of the smart logistics platform: a perspective of collaborative innovation participation," Annals of Operations Research, Springer, vol. 324(1), pages 893-935, May.
    2. Rui Ren & Wanjie Hu & Jianjun Dong & Bo Sun & Yicun Chen & Zhilong Chen, 2019. "A Systematic Literature Review of Green and Sustainable Logistics: Bibliometric Analysis, Research Trend and Knowledge Taxonomy," IJERPH, MDPI, vol. 17(1), pages 1-25, December.
    3. Xiao, Haohan & Xu, Min & Wang, Shuaian, 2023. "A game-theoretic model for crowd-shipping operations with profit improvement strategies," International Journal of Production Economics, Elsevier, vol. 262(C).
    4. Chung, Sai-Ho, 2021. "Applications of smart technologies in logistics and transport: A review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).
    5. Ghaderi, Hadi & Zhang, Lele & Tsai, Pei-Wei & Woo, Jihoon, 2022. "Crowdsourced last-mile delivery with parcel lockers," International Journal of Production Economics, Elsevier, vol. 251(C).
    6. Hao Liu & Haodong Chen & Hengyi Zhang & Haibin Liu & Xingwang Yu & Shiqing Zhang, 2022. "Contract Design of Logistics Service Supply Chain Based on Smart Transformation," Sustainability, MDPI, vol. 14(10), pages 1-17, May.
    7. Hongyan Dai & Peng Liu, 2020. "Workforce planning for O2O delivery systems with crowdsourced drivers," Annals of Operations Research, Springer, vol. 291(1), pages 219-245, August.
    8. Kexin Bi & Mengke Yang & Latif Zahid & Xiaoguang Zhou, 2020. "A New Solution for City Distribution to Achieve Environmental Benefits within the Trend of Green Logistics: A Case Study in China," Sustainability, MDPI, vol. 12(20), pages 1-25, October.
    9. Bathke, Henrik & Hartmann, Evi, 2021. "Accepting a crowdsourced delivery - A choice-based conjoint analysis," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Adapting to the Future: Maritime and City Logistics in the Context of Digitalization and Sustainability. Proceedings of the Hamburg International Conf, volume 32, pages 65-95, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.

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