IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0249543.html
   My bibliography  Save this article

Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse

Author

Listed:
  • Jianglong Yang
  • Li Zhou
  • Huwei Liu

Abstract

The utilization of a storage space can be considerably improved by using dense mobile racks. However, it is necessary to perform an optimisation study on the order picking to reduce the time cost as much as possible. According to the channel location information that needs to be sorted, the multiple orders are divided into different batches by using hierarchical clustering. On this basis, a mathematical model for the virtual order clusters formed in the batches is established to optimize the order cluster picking and rack position movement, with the minimum picking time as the objective. For this model, a hybrid genetic algorithm is designed, and the characteristics of the different examples and solution algorithms are further analysed to provide a reference for the solution of the order picking optimisation problem in a dense mobile rack warehouse.

Suggested Citation

  • Jianglong Yang & Li Zhou & Huwei Liu, 2021. "Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-25, April.
    • Handle: RePEc:plo:pone00:0249543
    DOI: 10.1371/journal.pone.0249543
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249543
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0249543&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0249543?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Nima Zaerpour & Yugang Yu & René B. M. de Koster, 2017. "Response time analysis of a live-cube compact storage system with two storage classes," IISE Transactions, Taylor & Francis Journals, vol. 49(5), pages 461-480, May.
    2. Tang, Jinjun & Yang, Yifan & Qi, Yong, 2018. "A hybrid algorithm for Urban transit schedule optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 745-755.
    3. Yugang Yu & René de Koster, 2009. "Optimal zone boundaries for two-class-based compact three-dimensional automated storage and retrieval systems," IISE Transactions, Taylor & Francis Journals, vol. 41(3), pages 194-208.
    4. Boysen, Nils & Briskorn, Dirk & Emde, Simon, 2016. "Sequencing of picking orders in mobile rack warehouses," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 83412, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. Masoud Mirzaei & René B.M. De Koster & Nima Zaerpour, 2017. "Modelling load retrievals in puzzle-based storage systems," International Journal of Production Research, Taylor & Francis Journals, vol. 55(21), pages 6423-6435, November.
    6. Patrick J. Reilly & Jennifer A. Pazour & Kellie R. Schneider, 2017. "Propagation of unit location uncertainty in dense storage environments," International Journal of Production Research, Taylor & Francis Journals, vol. 55(18), pages 5435-5449, September.
    7. Gianluca Nastasi & Valentina Colla & Silvia Cateni & Simone Campigli, 2018. "Implementation and comparison of algorithms for multi-objective optimization based on genetic algorithms applied to the management of an automated warehouse," Journal of Intelligent Manufacturing, Springer, vol. 29(7), pages 1545-1557, October.
    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. 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.

    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. He, Jing & Liu, Xinglu & Duan, Qiyao & Chan, Wai Kin (Victor) & Qi, Mingyao, 2023. "Reinforcement learning for multi-item retrieval in the puzzle-based storage system," European Journal of Operational Research, Elsevier, vol. 305(2), pages 820-837.
    2. MA, Yunfeng & CHEN, Haoxun & YU, Yugang, 2022. "An efficient heuristic for minimizing the number of moves for the retrieval of a single item in a puzzle-based storage system with multiple escorts," European Journal of Operational Research, Elsevier, vol. 301(1), pages 51-66.
    3. Mofidi, Seyed Shahab & Pazour, Jennifer A. & Roy, Debjit, 2018. "Proactive vs. reactive order-fulfillment resource allocation for sea-based logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 66-84.
    4. Nima Zaerpour & Yugang Yu & René B.M. de Koster, 2017. "Optimal two-class-based storage in a live-cube compact storage system," IISE Transactions, Taylor & Francis Journals, vol. 49(7), pages 653-668, July.
    5. Azadeh, K. & de Koster, M.B.M. & Roy, D., 2017. "Robotized Warehouse Systems: Developments and Research Opportunities," ERIM Report Series Research in Management ERS-2017-009-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Liao, Shengli & Liu, Huan & Liu, Benxi & Liu, Tian & Li, Chonghao & Su, Huaying, 2023. "Solution framework for short-term cascade hydropower system optimization operations based on the load decomposition strategy," Energy, Elsevier, vol. 277(C).
    7. Büchel, Beda & Corman, Francesco, 2022. "Modeling conditional dependencies for bus travel time estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    8. Lingyu Zheng & Hao Ma & Zhongyu Wang, 2024. "Travel Time Estimation for Urban Arterials Based on the Multi-Source Data," Sustainability, MDPI, vol. 16(17), pages 1-15, September.
    9. Wenquan Dong & Mingzhou Jin & Yanyan Wang & Peter Kelle, 2021. "Retrieval scheduling in crane-based 3D automated retrieval and storage systems with shuttles," Annals of Operations Research, Springer, vol. 302(1), pages 111-135, July.
    10. Gao, Yuhong & Qu, Zhaowei & Song, Xianmin & Yun, Zhenyu & Xia, Yingji, 2021. "A novel relationship model between signal timing, queue length and travel speed," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    11. Emrah B. Edis & Ozlem Uzun Araz & Ozgur Eski & Rahime Sancar Edis, 2023. "Storage location assignment of steel coils in a manufacturing company: an integer linear programming model and a greedy randomized adaptive search procedure," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 67-109, April.
    12. Lu Zhen & Jingwen Wu & Haolin Li & Zheyi Tan & Yingying Yuan, 2023. "Scheduling multiple types of equipment in an automated warehouse," Annals of Operations Research, Springer, vol. 322(2), pages 1119-1141, March.
    13. Nicolas Kirchner-Bossi & Fernando Porté-Agel, 2021. "Wind Farm Area Shape Optimization Using Newly Developed Multi-Objective Evolutionary Algorithms," Energies, MDPI, vol. 14(14), pages 1-25, July.
    14. Nima Zaerpour & Yugang Yu & René B. M. de Koster, 2017. "Response time analysis of a live-cube compact storage system with two storage classes," IISE Transactions, Taylor & Francis Journals, vol. 49(5), pages 461-480, May.
    15. Bukchin, Yossi & Raviv, Tal, 2022. "A comprehensive toolbox for load retrieval in puzzle-based storage systems with simultaneous movements," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 348-373.
    16. Yang, Jingjing & de Koster, René B.M. & Guo, Xiaolong & Yu, Yugang, 2023. "Scheduling shuttles in deep-lane shuttle-based storage systems," European Journal of Operational Research, Elsevier, vol. 308(2), pages 696-708.
    17. Boysen, Nils & Briskorn, Dirk & Emde, Simon, 2017. "Sequencing of picking orders in mobile rack warehouses," European Journal of Operational Research, Elsevier, vol. 259(1), pages 293-307.
    18. Tang, Jinjun & Chen, Xinqiang & Hu, Zheng & Zong, Fang & Han, Chunyang & Li, Leixiao, 2019. "Traffic flow prediction based on combination of support vector machine and data denoising schemes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    19. Hao, Jingjing & Zhang, Ling & Ji, Xiaofeng & Tang, Jinjun, 2020. "Modeling and analyzing of family intention for the customized student routes: A case study in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    20. Qu, T. & Huang, George Q. & Zhang, Yingfeng & Dai, Q.Y., 2010. "A generic analytical target cascading optimization system for decentralized supply chain configuration over supply chain grid," International Journal of Production Economics, Elsevier, vol. 127(2), pages 262-277, October.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0249543. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.