ABSTRACT
Artificial Intelligence (AI) based systems are normally data driven applications, where the model is trained to think on its own based on the external circumstances. Systems and literature of the past shows that AI based technologies are promising in intelligent supply chain management (SCM) and building resilient SCMs. There is a gap in literature which addresses on the framework for decision support systems in SCM and application of AI methods for building a robust Supply Chain Resilience (SCRs) leading to more exploration on the topic. In this paper, a decision framework is proposed by incorporating fuzzy logic and Recurrent Neural Networks (RNN) for disclosing the patterns of various AI enabled techniques for SCRs. The proposed analysis involved data from leading literatures to determine the most adoptable and significant applications of AI in SCRs. The analysis shows that techniques such as Fuzzy programming, network based algorithms and Genetic Algorithms has large impact on building SCRs. The results help in decision making by exhibiting an integrated framework which can help the AI practitioners for developing SCRs.
