IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i17p6310-d1229150.html
   My bibliography  Save this article

Design of an Intelligent Shop Scheduling System Based on Internet of Things

Author

Listed:
  • Maoyun Zhang

    (Faculty of Mechatronic Engineering, Changchun University of Science and Technology, Changchun 130022, China)

  • Yuheng Jiang

    (Faculty of Mechatronic Engineering, Changchun University of Science and Technology, Changchun 130022, China)

  • Chuan Wan

    (School of Information and Science and Technology, Northeast Normal University, Changchun 130024, China)

  • Chen Tang

    (Faculty of Mechatronic Engineering, Changchun University of Science and Technology, Changchun 130022, China)

  • Boyan Chen

    (Faculty of Mechatronic Engineering, Changchun University of Science and Technology, Changchun 130022, China)

  • Huizhuang Xi

    (Faculty of Mechatronic Engineering, Changchun University of Science and Technology, Changchun 130022, China)

Abstract

In order to optimize the functionality of automated guidance vehicles (AGVs) in logistics workshops, a wireless charging and task-based logistics intelligent dispatch system was developed based on the Internet of Things. This system aimed to improve freight efficiency in the workshop’s logistics system. The scheduling system successfully addressed the round-trip scheduling issue between AGVs and multiple tasks through two degrees of improvement: the application of AGVs and task path planning. To handle conflict coordination and AGV cluster path planning, a shortest path planning algorithm based on the A* search algorithm was proposed, and the traffic control law was enhanced. The initial population of genetic algorithms, which used greedy algorithms to solve problems, was found to be too large in terms of task distribution. To address this, the introduction of a few random individuals ensured population diversity and helped avoid local optima. Numerical experiments demonstrated a significantly accelerated convergence rate towards the optimal solution.

Suggested Citation

  • Maoyun Zhang & Yuheng Jiang & Chuan Wan & Chen Tang & Boyan Chen & Huizhuang Xi, 2023. "Design of an Intelligent Shop Scheduling System Based on Internet of Things," Energies, MDPI, vol. 16(17), pages 1-13, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6310-:d:1229150
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/17/6310/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/17/6310/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yuntao Zhao & Weigang Li & Xiao Wang & Chengxin Yi, 2019. "Path Planning of Slab Library Crane Based on Improved Ant Colony Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-16, August.
    2. Jianxun Li & Wenjie Cheng & Kin Keung Lai & Bhagwat Ram, 2022. "Multi-AGV Flexible Manufacturing Cell Scheduling Considering Charging," Mathematics, MDPI, vol. 10(19), pages 1-15, September.
    Full references (including those not matched with items on IDEAS)

    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. Yuan Gao & Qian Zhang & Chun Kit Lau & Bhagwat Ram, 2022. "Robust Appointment Scheduling in Healthcare," Mathematics, MDPI, vol. 10(22), pages 1-15, November.
    2. Zhuoling Jiang & Xiaodong Zhang & Pei Wang, 2023. "Grid-Map-Based Path Planning and Task Assignment for Multi-Type AGVs in a Distribution Warehouse," Mathematics, MDPI, vol. 11(13), pages 1-20, June.
    3. Qin Song, 2023. "Semi-Open Multi-Distribution Center Path Planning with Time Windows," Sustainability, MDPI, vol. 15(6), pages 1-14, March.

    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:jeners:v:16:y:2023:i:17:p:6310-:d:1229150. 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.