Supplier selection under fuzzy environment: A hybrid model using kam in DEA
In today’s competitive world, supplier selection is buzzword issue to business success for industries and firms. Robust methods are required to evaluate and select qualified suppliers. Regarding to the literature, the hybrid Data Envelopment Analysis-Artificial Intelligence (DEA-AI) models are the e...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/13607/1/SUPPLIER_SELECTION_UNDER_FUZZY_ENVIRONMENT.pdf |
| Summary: | In today’s competitive world, supplier selection is buzzword issue to business success for industries and firms. Robust methods are required to evaluate and select qualified suppliers. Regarding to the literature, the hybrid Data Envelopment Analysis-Artificial Intelligence (DEA-AI) models are the effective models to assess the suppliers’ performance. This paper proposes an integrating Kourosh and Arash Model (KAM) in DEA and Adaptive Fuzzy Inference System (ANFIS) as a powerful tool in prediction to estimate the supplier efficiency scores. This hybrid model consists of two parts. First part applies KAM to determine a best technical efficiency score for each supplier. Second part utilizes the suppliers’ performance score for training ANFIS to estimate the new suppliers’ performance. The proposed model implemented in a cosmetic industry, too. |
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