IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i17p7034-d405732.html
   My bibliography  Save this article

Data-Driven Design and Optimization for Smart Logistics Parks: Towards the Sustainable Development of the Steel Industry

Author

Listed:
  • Yaqiong Lv

    (School of Logistics Engineering, Wuhan University of Technology, Wuhan, Hubei 430070, China)

  • Shangjia Xiang

    (School of Logistics Engineering, Wuhan University of Technology, Wuhan, Hubei 430070, China)

  • Tianyi Zhu

    (School of Logistics Engineering, Wuhan University of Technology, Wuhan, Hubei 430070, China)

  • Shuzhu Zhang

    (Department of Information Management and Artificial Intelligence, Zhejiang University of Finance & Economics, Hangzhou, Zhejiang 310018, China)

Abstract

The design of steel logistics parks acts as fundamental infrastructure supporting the operations of storage, allocation, and distribution of steel products in the steel logistics industry, which actually lags behind the development of other logistics industries, such as e-commerce logistics, due to its large lot bulk storage, low turnover rate, and costly transportation and operations. This research proposes a data-driven approach for a specific steel logistics park, aiming to improve its operational efficiency in terms of product layout and allocation in multiple yards. The entry and delivery order data are analyzed comprehensively so as to determine the products with high operational frequency and the corresponding relevancy among them. Experimental results show that, among the 69 steel specifications, 14 high-frequency products are identified, and the correlation among the 14 identified high-frequency products possesses evident distribution characteristics concerning their brands and specifications. The identified frequency and correlation among various products can not only facilitate the product layout and allocation in steel logistics parks, but also advance the vehicle scheduling efficiency for product pick-up and delivery. Moreover, the research methodology and framework can provide managerial insights for other industries with mass data processing requirements.

Suggested Citation

  • Yaqiong Lv & Shangjia Xiang & Tianyi Zhu & Shuzhu Zhang, 2020. "Data-Driven Design and Optimization for Smart Logistics Parks: Towards the Sustainable Development of the Steel Industry," Sustainability, MDPI, vol. 12(17), pages 1-12, August.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:7034-:d:405732
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/17/7034/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/17/7034/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Julian Pinto & Manuel Morales & Mariia Fedoruk & Marina Kovaleva & Arnaud Diemer, 2019. "Servitization in Support of Sustainable Cities: What Are Steel’s Contributions and Challenges?," Post-Print hal-02127800, HAL.
    2. Julian T. M. Pinto & Manuel E. Morales & Mariia Fedoruk & Marina Kovaleva & Arnaud Diemer, 2019. "Servitization in Support of Sustainable Cities: What Are Steel’s Contributions and Challenges?," Sustainability, MDPI, vol. 11(3), pages 1-18, February.
    3. Kuo, R.J. & Pai, C.M. & Lin, R.H. & Chu, H.C., 2015. "The integration of association rule mining and artificial immune network for supplier selection and order quantity allocation," Applied Mathematics and Computation, Elsevier, vol. 250(C), pages 958-972.
    4. Hsieh, Ling-Feng & Huang, Yi-Chen, 2011. "New batch construction heuristics to optimise the performance of order picking systems," International Journal of Production Economics, Elsevier, vol. 131(2), pages 618-630, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sebastjan Lazar & Dorota Klimecka-Tatar & Matevz Obrecht, 2021. "Sustainability Orientation and Focus in Logistics and Supply Chains," Sustainability, MDPI, vol. 13(6), pages 1-20, March.
    2. Mustafa Qahtan Alsudani & Mustafa Musa Jaber & Mohammed Hasan Ali & Sura Khalil Abd & Ahmed Alkhayyat & Z. H. Kareem & Ahmed Rashid Mohhan, 2023. "RETRACTED ARTICLE: Smart logistics with IoT-based enterprise management system using global manufacturing," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-31, March.

    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. Luca Nitschke, 2020. "Reconstituting Automobility: The Influence of Non-Commercial Carsharing on the Meanings of Automobility and the Car," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
    2. Lapo Mola & Quentin Berger & Karoliina Haavisto & Isabella Soscia, 2020. "Mobility as a Service: An Exploratory Study of Consumer Mobility Behaviour," Sustainability, MDPI, vol. 12(19), pages 1-14, October.
    3. Paula Brezovec & Nina Hampl, 2021. "Electric Vehicles Ready for Breakthrough in MaaS? Consumer Adoption of E-Car Sharing and E-Scooter Sharing as a Part of Mobility-as-a-Service (MaaS)," Energies, MDPI, vol. 14(4), pages 1-25, February.
    4. Wim Coreynen & Arjen van Witteloostuijn & Johanna Vanderstraeten, 2021. "Toward Servitized Research: An Integrated Approach for Sustainable Product-Service Innovation," Sustainability, MDPI, vol. 13(15), pages 1-21, July.
    5. Shen-Tsu Wang, 2016. "Integrating grey sequencing with the genetic algorithm--immune algorithm to optimise touch panel cover glass polishing process parameter design," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4882-4893, August.
    6. Dobromir Herzog, 2021. "Human factor aspects in information security management in the traditional IT and cloud computing models," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(2), pages 93-108.
    7. Silva, Allyson & Coelho, Leandro C. & Darvish, Maryam & Renaud, Jacques, 2020. "Integrating storage location and order picking problems in warehouse planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    8. Pan, Jason Chao-Hsien & Shih, Po-Hsun & Wu, Ming-Hung, 2015. "Order batching in a pick-and-pass warehousing system with group genetic algorithm," Omega, Elsevier, vol. 57(PB), pages 238-248.
    9. Agapito, Giuseppe & Guzzi, Pietro Hiram & Cannataro, Mario, 2019. "Parallel extraction of association rules from genomics data," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 434-446.
    10. Zhitao Xu & Adel Elomri & Roberto Baldacci & Laoucine Kerbache & Zhenyong Wu, 2024. "Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective," Annals of Operations Research, Springer, vol. 338(2), pages 1359-1401, July.
    11. Chen, Tzu-Li & Cheng, Chen-Yang & Chen, Yin-Yann & Chan, Li-Kai, 2015. "An efficient hybrid algorithm for integrated order batching, sequencing and routing problem," International Journal of Production Economics, Elsevier, vol. 159(C), pages 158-167.
    12. Boysen, Nils & de Koster, René & Weidinger, Felix, 2019. "Warehousing in the e-commerce era: A survey," European Journal of Operational Research, Elsevier, vol. 277(2), pages 396-411.
    13. Cheng, Chen-Yang & Chen, Yin-Yann & Chen, Tzu-Li & Jung-Woon Yoo, John, 2015. "Using a hybrid approach based on the particle swarm optimization and ant colony optimization to solve a joint order batching and picker routing problem," International Journal of Production Economics, Elsevier, vol. 170(PC), pages 805-814.
    14. Fangyu Chen & Yongchang Wei & Hongwei Wang, 2018. "A heuristic based batching and assigning method for online customer orders," Flexible Services and Manufacturing Journal, Springer, vol. 30(4), pages 640-685, December.
    15. Ouyang, Zhiyuan & Leung, Eric K.H. & Huang, George Q., 2023. "Community logistics and dynamic community partitioning: A new approach for solving e-commerce last mile delivery," European Journal of Operational Research, Elsevier, vol. 307(1), pages 140-156.
    16. Minfang Huang & Qiong Guo & Jing Liu & Xiaoxu Huang, 2018. "Mixed Model Assembly Line Scheduling Approach to Order Picking Problem in Online Supermarkets," Sustainability, MDPI, vol. 10(11), pages 1-16, October.
    17. Ardjmand, Ehsan & Shakeri, Heman & Singh, Manjeet & Sanei Bajgiran, Omid, 2018. "Minimizing order picking makespan with multiple pickers in a wave picking warehouse," International Journal of Production Economics, Elsevier, vol. 206(C), pages 169-183.
    18. Çağla Cergibozan & A. Serdar Tasan, 2019. "Order batching operations: an overview of classification, solution techniques, and future research," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 335-349, January.
    19. Pardo, Eduardo G. & Gil-Borrás, Sergio & Alonso-Ayuso, Antonio & Duarte, Abraham, 2024. "Order batching problems: Taxonomy and literature review," European Journal of Operational Research, Elsevier, vol. 313(1), pages 1-24.
    20. Zhang, Guoqing & Shang, Xiaoting & Alawneh, Fawzat & Yang, Yiqin & Nishi, Tatsushi, 2021. "Integrated production planning and warehouse storage assignment problem: An IoT assisted case," International Journal of Production Economics, Elsevier, vol. 234(C).

    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:jsusta:v:12:y:2020:i:17:p:7034-:d:405732. 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.