Decision Support Systems Based on Artificial Intelligence for Supply Chain Management: A Literature Review

The aim of this paper is to provide an overview of the integration of artificial intelligence (IA) in decision support systems (DSS) to solve problems related to the Supply Chain Management (SCM). Non-intelligent DSS approaches based on traditional methods are unable to handle unstructured data, and they face great difficulties in describing non-linear relationships. Looking for intelligent solutions that are able to overcome these difficulties is becoming increasingly important and has led to a new trend of adding intelligence capability to DSS. Many efforts have been devoted to propose intelligent decision support systems for SCM. To shed light on the degree of AI integration in DSS in this context, we present a literature review highlighting the following results: (a) AI integration in DSS for SCM was still in the development stage, (b) multi-agent systems and machine learning are the most used AI techniques and methods in DSS, and (c) risk management and performance improvement are the most covered activities in intelligent DSS.