IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/5997095.html
   My bibliography  Save this article

Integrated Optimization of Input/Output Point Assignment and Twin Stackers Scheduling in Multi-Input/Output Points Automated Storage and Retrieval System by Ant Colony Algorithm

Author

Listed:
  • Yubo Song
  • Haibo Mu
  • Muazzam Maqsood

Abstract

This paper researches the problem of operational optimization in the multiple-input/output (multi-I/O) points automated storage and retrieval system (AS/RS), where the destination addresses of the retrieval requests are unknown, twin stackers work simultaneously in the same aisle and cannot cross each other, and each stacker can carry two cargo units at the same time. The problem is formalized as an integrated optimization problem with noncrossing constraint for the I/O point assignment and the storage/retrieval (S/R) requests grouping and scheduling. The complexity of the problem is analyzed without considering the I/O point assignment and double units transport (DUT). In order to adapt to the integrated optimization characteristics of the problem, a node structure with multi-I/O points is considered, and the probability selection formula of ant colony algorithm is improved for multiple pheromones. Various numerical experiments show that the average deviation of the objective function value between the proposed method and CPLEX is no more than 0.4%, and the maximum deviation is only 1.22%. Although the phased algorithm avoids the waiting of stacker in operation, the average value of its objective function is 12.14% higher than that of the proposed method, and the maximum deviation is more than 30%.

Suggested Citation

  • Yubo Song & Haibo Mu & Muazzam Maqsood, 2022. "Integrated Optimization of Input/Output Point Assignment and Twin Stackers Scheduling in Multi-Input/Output Points Automated Storage and Retrieval System by Ant Colony Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-18, May.
  • Handle: RePEc:hin:jnlmpe:5997095
    DOI: 10.1155/2022/5997095
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/mpe/2022/5997095.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/mpe/2022/5997095.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2022/5997095?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
    ---><---

    Citations

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


    Cited by:

    1. Jiansha Lu & Lili Xu & Jinghao Jin & Yiping Shao, 2022. "A Mixed Algorithm for Integrated Scheduling Optimization in AS/RS and Hybrid Flowshop," Energies, MDPI, vol. 15(20), pages 1-17, 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:hin:jnlmpe:5997095. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.