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

  • 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.

     

     

  • References

    1. [1] D. V. Ramana, K. N. Rao, and J. S. Kumar, "A Critical Review on Supply Chain Strategies and their Performance," International Journal of Engineering Science and Computing (IJESC), vol. 6, pp. 4525-4545, (2016).

      [2] B. Marchi and S. Zanoni, "Supply Chain Management for Improved Energy Efficiency: Review and Opportunities," Energies, vol. 10, p. 1618, 16 October (2017).

      [3] C. D. Singh, R. Singh, J. S. Mand, and S. Singh, "Application of Lean and JIT Principles in Supply Chain Management," International Journal of Management Research and Business Strategy (IJMRBS), vol. 2, (2013).

      [4] B. .V. and L. S.N., "An Analysis on Agile Manufacturing System," SSRG International Journal of Industrial Engineering (SSRG-IJIE) vol. 2, pp. 36-40, 3 May (2015).

      [5] H. R. Susana Azevedo, Virgilio Cruz-Machado, "Trade-offs among Lean, Agile, Resilient and Green Paradigms in Supply Chain Management: A Case Study Approach," in Proceeding of the Seventh International Conference on Management Science and Engineering Management, (2014), pp. 953-968.

      [6] V. P. Rajeev Kant, L. N. Pattanaik, "Lean, Agile & Leagile Supply Chain: A Comparative Study," ELK Asia Pacific Journals –Special Issue, (2016).

      [7] R. K. Gavade, "Multi-Criteria Decision Making: An overview of different selection problems and methods," International Journal of Computer Science and Information Technologies (IJCSIT), vol. 5, pp. 5643-5646, 2014.

      [8] A. A. Esfahani, H. Ahmadi, M. Nilashi, M. Alizadeh, A. Bashiri, M. Abbasi Farajzadeh, L. Shahmoradi, H. R. Rasouli, and M. Hekmat, "An evaluation model for the implementation of hospital information system in public hospitals using multi-criteria-decision-making (MCDM) approaches," International Journal of Engineering & Technology (IJET), vol. 7, p. 1, 2017.

      [9] L. Fei, Y. Hu, F. Xiao, L. Chen, and Y. Deng, "A Modified TOPSIS Method Based onDNumbers and Its Applications in Human Resources Selection," Mathematical Problems in Engineering, vol. 2016, pp. 1-14, 2016.

      [10] F. Ho, S. Abdul-Rashid, and R. Raja Ghazilla, "Analytic Hierarchy Process-Based Analysis to Determine the Barriers to Implementing a Material Efficiency Strategy: Electrical and Electronics’ Companies in the Malaysian Context," Sustainability, vol. 8, p. 1035, 2016.

      [11] M. Ibrohim and Sumiati, "Decision Support System for Determining the Scholarship Recipients using Simple Additive Weighting (SAW)," International Journal of Computer Applications (IJCA), vol. 151, pp. 10-13, October, (2016).

      [12] N. L. H. T. T. Quyen, P. T. Nguyen, and V. D. B. Huynh, "A hybrid multi criteria decision analysis for engineering project manager evaluation," International Journal of ADVANCED AND APPLIED SCIENCES (IJASE), vol. 4, pp. 49-52, 2017.

      [13] P.Venkateswarlu and B. D. Sarma, "Selection of Equipment by Using SAW and Vikor Methods," International Journal of Engineering Research and Application (IJERA), vol. 6, pp. 61-68, (2016).

      [14] Purnawansyah and Haviluddin, "K-Means Clustering Implementation in Network Traffic Activities," in 2016 International Conference on Computational Intelligence and Cybernetics, Makassar, Indonesia, 2016, pp. 51-54.

      [15] Purnawansyah, Haviluddin, A. F. O. Gafar, and I. Tahyudin, "Comparison between K-Means and Fuzzy C-Means Clustering in Network Traffic Activities," in 2017 International Conference on Management Science and Engineering Management (ICMSEM), 2017.

      [16] X. Li, Y. Fan, J. W. Shaw, and Y. Qi, "A Fuzzy AHP Approach to Compare Transit System Performance in US Urbanized Areas," Journal of Public Transportation, vol. 20, (2017).

      [17] B. Suprapty, R. Malani, and O. D. Nurhayati, "Design of Information System for Acceptance Selection of Prospective Employees Online Using Tahani Fuzzy Logic Method and Simple Additive Weighting (SAW)," International Journal of Computing and Informatics (IJCANDI) vol. 1, pp. 17-28, (2016).

      [18] C.-M. Lai, J.-L. Hung, and C.-C. Chen, "A Fuzzy Analytic Network Process for Criteria Evaluation of Sportwear Design and Development," International Journal of Management and Applied Science (IJMAS), vol. 2, pp. 45-49, 2016.

      [19] Y. O. Ouma, J. Opudo, and S. Nyambenya, "Comparison of Fuzzy AHP and Fuzzy TOPSIS for Road Pavement Maintenance Prioritization: Methodological Exposition and Case Study," Advances in Civil Engineering, vol. 2015, pp. 1-17, (2015).

      [20] P. Sona, T. Johnson, and C. Vijayalakshmi, "Design of a multi criteria decision model-fuzzy analytical hierarchy approach," International Journal of Engineering & Technology (IJET), vol. 7, pp. 116-120, (2018).

      [21] C. Wang, Q. Li, X. Zhou, and T. Yang, "Hesitant Triangular Fuzzy Information Aggregation Operators Based on Bonferroni Means and Their Application to Multiple Attribute Decision Making," The Scientific World Journal, vol. 2014, pp. 1-15, (2014).

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    ., 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