Selection of the best supply chain strategy using fuzzy based decision model

  • Authors

    • Surahman .
    • Arkas Viddy
    • Achmad Fanany Onnilita Gaffar
    • Haviluddin .
    • Ansari Saleh Ahmar
    2018-03-05
    https://doi.org/10.14419/ijet.v7i2.2.12748
  • supply chain strategy, Fuzzy MCDM, strategy selection

  • Abstract

    The right strategy in the supply chain has become strategic issues are important today because the nature of these decisions is usually complex and unstructured. There are many quantitative and qualitative attributes such as cost, responsiveness, and flexibility that need to be taken into account to determine the best supply chain strategy. Assessment of all attributes as mentioned is usually through a human evaluation process involving many subjectivity and uncertainty factors. In addition, the complexity of the problems directly related to each attribute used as an assessment increases the problem of uncertainty. Fuzzy MCDM (Multi Criteria Decision Making) is one of the MCDM methods that use a fuzzy approach to overcome complexity and uncertainty of the problem. Today the market has been able to witness a worldwide expansion and dynamic situation by leveraging new innovations in production methodology and information technology. With this new innovation, the market can increase demand for products tailored to minimum cost with minimum waiting time. Lean and agile are two chain strategy concepts evolved in the pursuit of business excellence, while the concept of leagile is in between. This study aims to select the best supply chain strategy (lean, leagile, agile) at a manufacturing company in Samarinda – East Kalimantan based on certain criteria by using Fuzzy MCDM.

     

     

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  • How to Cite

    ., S., Viddy, A., Fanany Onnilita Gaffar, A., ., H., & Saleh Ahmar, A. (2018). Selection of the best supply chain strategy using fuzzy based decision model. International Journal of Engineering & Technology, 7(2.2), 117-121. https://doi.org/10.14419/ijet.v7i2.2.12748

    Received date: 2018-05-12

    Accepted date: 2018-05-12

    Published date: 2018-03-05