Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource An Empirical Framework Using Weighted Feed Forward Neural Network for Supply Chain Resilience (SCR) Strategy Selection Subject The topic of the resource Artificial Intelligence (AI); Fuzzy Programming and Multi-Level Decision Support (MLDS) framework; Supply Chain Management (SCM); Supply Chain Resilience (SCR) Description An account of the resource 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. The power of AI has reached every facet of business and common life and is even being largely explored to be adopted in life sciences and medical domains. It supports the human in decision-making through the cognitive utilities which arises out of self-learning capabilities of a model. With the exponential growth of data, supply chain management and analytics have attracted a large community of researchers to build intelligent systems which can lead to re-invention of data-driven decision systems powered by AI. 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 (SCR) 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 programing, network based algorithms, and genetic algorithms have 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. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. Creator An entity primarily responsible for making the resource Rajagopal M.; Sivasakthivel R. Source A related resource from which the described resource is derived Operations Research Forum, Vol-5, No. 2 Publisher An entity responsible for making the resource available Springer International Publishing Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s43069-024-00313-z" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s43069-024-00313-z</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189963474&amp;doi=10.1007%2Fs43069-024-00313-z&amp;partnerID=40&amp;md5=978593c9b896645391109ec527e16c99" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189963474&amp;doi=10.1007%2fs43069-024-00313-z&amp;partnerID=40&amp;md5=978593c9b896645391109ec527e16c99</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 26622556 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Rajagopal M., School of Business and Management, Lean Operations and Systems, CHRIST (Deemed to be University), Bangalore, India; Sivasakthivel R., Department of Computer Science, School of Sciences, CHRIST (Deemed to be University), Bangalore, India