IDEAS home Printed from https://ideas.repec.org/a/igg/jswis0/v19y2023i1p1-23.html
   My bibliography  Save this article

Web Semantic-Based MOOP Algorithm for Facilitating Allocation Problems in the Supply Chain Domain

Author

Listed:
  • Chun-Yuan Lin

    (Asia University, Taiwan)

  • Mosiur Rahaman

    (Asia University, Taiwan)

  • Massoud Moslehpour

    (Asia University, Taiwan)

  • Sourasis Chattopadhyay

    (Asia University, Taiwan)

  • Varsha Arya

    (Department of Business Administration, Asia University, Taiwan, & Lebanese American University, Beirut, Lebanon, & Center for Interdisciplinary Research, University of Petroleum and Energy Studies (UPES), Dehradun, India)

Abstract

The facility allocation of the supply chain is critical since it directly influences cost efficiency, customer service, supply chain responsiveness, risk reduction, network optimization, and overall competitiveness. When enterprises deploy their facilities wisely, they may achieve operational excellence, exceed customer expectations, and obtain a competitive advantage in today's volatile business climate. Due to this reason, a multi-objective facility allocation problem is introduced in this research with cooperative-based multi-level backup coverage considering distance-based facility attractiveness. The facility of the coverage is further described as two different layers of the coverage process, where demand can be covered as full, partial, and no coverage by their respective facilities. The main objectives of this facility allocation problem are to maximize the coverage of the facility to maximize overall facility coverage in the supply chain network and simultaneously minimize the overall cost.

Suggested Citation

  • Chun-Yuan Lin & Mosiur Rahaman & Massoud Moslehpour & Sourasis Chattopadhyay & Varsha Arya, 2023. "Web Semantic-Based MOOP Algorithm for Facilitating Allocation Problems in the Supply Chain Domain," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 19(1), pages 1-23, January.
  • Handle: RePEc:igg:jswis0:v:19:y:2023:i:1:p:1-23
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSWIS.330250
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Han, Jialin & Zhang, Jiaxiang & Zeng, Bing & Mao, Mingsong, 2021. "Optimizing dynamic facility location-allocation for agricultural machinery maintenance using Benders decomposition," Omega, Elsevier, vol. 105(C).
    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. Tang, Lianhua & Li, Yantong & Bai, Danyu & Liu, Tao & Coelho, Leandro C., 2022. "Bi-objective optimization for a multi-period COVID-19 vaccination planning problem," Omega, Elsevier, vol. 110(C).
    2. Zhu, Xuedong & Son, Junbo & Zhang, Xi & Wu, Jianguo, 2023. "Constraint programming and logic-based Benders decomposition for the integrated process planning and scheduling problem," Omega, Elsevier, vol. 117(C).
    3. Raoul Fonkoua Fofou & Zhigang Jiang & Qingshan Gong & Yihua Yang, 2022. "A Decision-Making Model for Remanufacturing Facility Location in Underdeveloped Countries: A Capacitated Facility Location Problem Approach," Sustainability, MDPI, vol. 14(22), pages 1-18, November.
    4. Kidd, Martin P. & Darvish, Maryam & Coelho, Leandro C. & Gendron, Bernard, 2024. "A relax-and-restrict matheuristic for supply chain network design with facility location and customer due date flexibility," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    5. Kahr, Michael, 2022. "Determining locations and layouts for parcel lockers to support supply chain viability at the last mile," Omega, Elsevier, vol. 113(C).
    6. Rahmati, Reza & Neghabi, Hossein & Bashiri, Mahdi & Salari, Majid, 2023. "Stochastic regional-based profit-maximizing hub location problem: A sustainable overview," Omega, Elsevier, vol. 121(C).

    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:igg:jswis0:v:19:y:2023:i:1:p:1-23. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.