文章基本信息

标题：Sustainable Supplier Selection based on Self-organizing Map Neural Network and Multi Criteria Decision Making Approaches
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作者：Amir Hossein Azadnia ; Amir Hossein Azadnia ; Muhamad Zameri Mat Saman 等
期刊名称：Procedia - Social and Behavioral Sciences
印刷版ISSN：1877-0428
出版年度：2012
卷号：65
页码：879-884
DOI：10.1016/j.sbspro.2012.11.214
语种：English
出版社：Elsevier
摘要：AbstractDue 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.
关键词：Sustainability;Supplier selection;Self-organizing map;Multi-criteria decision making