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    Sustainable Supplier Selection based on Self-organizing Map Neural Network and Multi Criteria Decision Making Approaches


    Azadnia, Amir Hossein, Saman, Muhamad Zameri Mat, Wong, Kuan Yew, Ghadimi, Pezhman and Zakuan, Norhayati (2012) Sustainable Supplier Selection based on Self-organizing Map Neural Network and Multi Criteria Decision Making Approaches. Procedia - Social and Behavioral Sciences, 65. pp. 879-884. ISSN 1877-0428

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    Abstract

    Due to increasing public awareness, government regulation and market pressure on sustainability issues, companies have found out that in order to have a competitive edge, sustainable operational activities should be adopted with their supply chain. Sustainable supplier selection as a crucial decision can affect the overall degree of sustainability in a supply chain. In this paper, an integrated approach of clustering and multi criteria decision making methods have been proposed in order to solve sustainable supplier selection problem. Firstly, self- organizing map as one of the well-known neural network methods has been utilized in order to cluster and prequalify the suppliers based on customer demand attribute and sustainability elements. Then, multi criteria decision making methods will be utilized in order to rank the cluster of suppliers to make coordination between them and customers. A case study has been carried out in order to show the efficiency of proposed approach.
    Item Type: Article
    Keywords: Sustainability; supplier selection; self-organizing map; multi-criteria decision making;
    Academic Unit: Faculty of Social Sciences > School of Business
    Item ID: 15914
    Identification Number: 10.1016/j.sbspro.2012.11.214
    Depositing User: Amir Azadnia
    Date Deposited: 04 May 2022 10:46
    Journal or Publication Title: Procedia - Social and Behavioral Sciences
    Publisher: Elsevier
    Refereed: Yes
    Related URLs:
    URI: https://mural.maynoothuniversity.ie/id/eprint/15914
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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