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...

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Main Authors: Fallahpour, A., Olugu, E.U., Musa, S.N., Khezrimotlagh, D., Singh, S.
Format: Conference or Workshop Item
Language:English
Published: 2014
Subjects:
Online Access:http://eprints.um.edu.my/13607/1/SUPPLIER_SELECTION_UNDER_FUZZY_ENVIRONMENT.pdf
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author Fallahpour, A.
Olugu, E.U.
Musa, S.N.
Khezrimotlagh, D.
Singh, S.
author_facet Fallahpour, A.
Olugu, E.U.
Musa, S.N.
Khezrimotlagh, D.
Singh, S.
author_sort Fallahpour, A.
collection UM
description 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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spelling um.eprints-136072015-06-17T01:59:07Z http://eprints.um.edu.my/13607/ Supplier selection under fuzzy environment: A hybrid model using kam in DEA Fallahpour, A. Olugu, E.U. Musa, S.N. Khezrimotlagh, D. Singh, S. TJ Mechanical engineering and machinery 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. 2014-04 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.um.edu.my/13607/1/SUPPLIER_SELECTION_UNDER_FUZZY_ENVIRONMENT.pdf Fallahpour, A. and Olugu, E.U. and Musa, S.N. and Khezrimotlagh, D. and Singh, S. (2014) Supplier selection under fuzzy environment: A hybrid model using kam in DEA. In: Proceedings of the 12th International Conference of DEA, 14-17 Apr 2014, Kuala Lumpur.
spellingShingle TJ Mechanical engineering and machinery
Fallahpour, A.
Olugu, E.U.
Musa, S.N.
Khezrimotlagh, D.
Singh, S.
Supplier selection under fuzzy environment: A hybrid model using kam in DEA
title Supplier selection under fuzzy environment: A hybrid model using kam in DEA
title_full Supplier selection under fuzzy environment: A hybrid model using kam in DEA
title_fullStr Supplier selection under fuzzy environment: A hybrid model using kam in DEA
title_full_unstemmed Supplier selection under fuzzy environment: A hybrid model using kam in DEA
title_short Supplier selection under fuzzy environment: A hybrid model using kam in DEA
title_sort supplier selection under fuzzy environment a hybrid model using kam in dea
topic TJ Mechanical engineering and machinery
url http://eprints.um.edu.my/13607/1/SUPPLIER_SELECTION_UNDER_FUZZY_ENVIRONMENT.pdf
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