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An Improved Hybrid Model for Order Quantity Allocation and Supplier Risk Exposure

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  • Peh Sang Ng

    (Department of Physical and Mathematical Science, Faculty of Science, Universiti Tunku Abdul Rahman, Jalan Universiti, Perak, Malaysia)

  • Feng Zhang

    (Key Laboratory in Machine Learning and Computational Intelligence of Hebei Province, College of Mathematics and Information Science, Hebei University, Hebei, China)

Abstract

This paper investigates the risk exposure arising from the supplier evaluation criteria of cost, quality, delivery, and flexibility. An integrated method of Fuzzy Decision Making Trial and Evaluation Laboratory (FDEMATEL) and Fuzzy Analytical Network Process (FANP), which is able to address interaction and feedback effects between the criteria and subjectivity in the decision rating, is used to generate the importance weights of the objectives for a network relationship problem. Different weights of the objectives are then incorporated into a Fuzzy Multi-Objective Programming (FMOP) model for determining the optimal order quantity allocated to the suppliers. The proposed method provides a more realistic decision making scenario by considering different importance weights of criteria from individual priority. Therefore, it provides a practical method to solve the real world problems. The validity of the proposed method is illustrated by a case study from a trading company.

Suggested Citation

  • Peh Sang Ng & Feng Zhang, 2016. "An Improved Hybrid Model for Order Quantity Allocation and Supplier Risk Exposure," International Journal of Fuzzy System Applications (IJFSA), IGI Global Scientific Publishing, vol. 5(3), pages 120-147, July.
    • Handle: RePEc:igg:jfsa00:v:5:y:2016:i:3:p:120-147
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