Supplier selection for smart supply chain: An adaptive fuzzy-neuro approach
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AbstractIn recent years, companies have experienced international changes that have occurred as a result of technological advances, market globalization, or natural disasters. So, organizations are trying to improve their performance in order to be more competitive. In other words, organizations’ competitiveness highly depends on their suppliers. At present, companies need to consider and include so-called ‘resilience’, ‘sustainability’, and ‘smartness’ in the supplier’s selection to retain a competitive advantage. In this context, the purpose of this paper is to present an intelligent decision-making model for selecting the appropriate suppliers. For doing so, a set of criteria evaluation was determined to respond to the novel era circumstances. The suggested work is helpful for academics as well as professionals as it emphasizes the importance of resilient-sustainable supplier selection in the digital era.
CitationZekhnini, K., Cherrafi, A., Bouhaddou, I., Benghabrit, Y., Garza-Reyes, J.A. (2020). 'Supplier selection for smart supply chain: An adaptive fuzzy-neuro approach'. 5th North America International Conference on Industrial Engineering and Operations Management (IEOM), Detroit, MI, US, August 10-14. Michigan: IEOM, pp. 1-9.
JournalProceedings of the 5th North America International Conference on Industrial Engineering and Operations Management (IEOM)
TypeMeetings and Proceedings
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