Application of adaptive neuro fuzzy inference system in measurement of supply chain agility: Real case study of a manufacturing company


S. M. Seyedhoseini, J. Jassbi and N. Pilevari*

In this paper we have developed an approach based on Adaptive Neuro Fuzzy Inference System (ANFIS) for measurement of agility in Supply Chain. An Agile Supply Chain (ASC) is frequently considered as a dominant competitive advantage. As complexity and vagueness of agility in global markets must be considered as one of the essential characteristics of an ASC system, we efficiently applied ANFIS in order to inject different and complicated agility capabilities (that is, flexibility, competency, cost, responsiveness and quickness) to the model in an ambiguous environment. Moreover, different potential attributes of ANFIS (that is, considering membership functions for each agility capabilities, training these functions through an adaptive procedure, using fuzzy concepts in order to model objective attributes) made the proposed approach meritorious for surveying real life problems. To our best knowledge such application has been never reported for ASC and ANFIS in literature. It has worth noting that application of the proposed procedure as a Decision Support System (DSS) helps managers to perform gap analysis between existent agility level and the desired one and also provides reliable information for decision making. The proposed procedure has efficiently been applied to a large scale automobile manufacturing company in Iran. Statistical analysis represent that there are no meaningful difference between experts’ opinion and our proposed procedure for supply chain agility measurement.


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