IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/8218709.html
   My bibliography  Save this article

Multiobjective Sustainable Order Allocation Problem Optimization with Improved Genetic Algorithm Using Priority Encoding

Author

Listed:
  • Zhiqiang Fan
  • Shanshan Li
  • Zhijun Gao

Abstract

Recently, incorporating carbon emissions into order allocation decisions has attracted considerable attention among scholars and industrialists. Moreover, affected by the random fluctuations of the man, machine, material, method, and environment (4M1E), the production process is usually imperfect with defective products. Reducing product defective rates can effectively improve the quality of the order allocation process. Therefore, considering product defective rate and carbon emission, a multiobjective integer nonlinear programming (INLP) formulation is presented to address this multiproduct, multiperiod, and multi-OEM order allocation problem. Furthermore, exploring the existing literatures, an improved genetic algorithm using priority encoding (IGAUPE) is put forward as a novel optimization technique. Finally, numerical experiments are conducted to validate the correctness of the proposed INLP model as well as the effectiveness of the proposed algorithm. Compared with the genetic algorithm using binary encoding (GAUBE), genetic algorithm using two-layer encoding (GAUTE), and LINGO software, the experiment results show that IGAUPE can improve the efficiency and effectiveness within the predetermined time limit when solving large-scale instances.

Suggested Citation

  • Zhiqiang Fan & Shanshan Li & Zhijun Gao, 2019. "Multiobjective Sustainable Order Allocation Problem Optimization with Improved Genetic Algorithm Using Priority Encoding," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-12, November.
    • Handle: RePEc:hin:jnlmpe:8218709
    DOI: 10.1155/2019/8218709
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2019/8218709.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2019/8218709.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2019/8218709?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. Raja Awais Liaqait & Salman Sagheer Warsi & Taiba Zahid & Usman Ghafoor & Muhammad Shakeel Ahmad & Jeyraj Selvaraj, 2021. "A Decision Framework for Solar PV Panels Supply Chain in Context of Sustainable Supplier Selection and Order Allocation," Sustainability, MDPI, vol. 13(23), pages 1-25, November.

    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:8218709. 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.