This paper presents a systematic review of studies related to artificial intelligence (AI)
applications in supply chain management (SCM). Our systematic search of the related …

Industry 4.0 connotes a new industrial revolution centered around cyber-physical systems. It
posits that the real-time connection of physical and digital systems, along with new enabling …

The effect of big data on the lean, agile, resilient, and green (LARG) supply chain has not
been explored much in the literature. This study investigates the role of 'Big Data …

We develop a data-driven decision model to improve process quality in manufacturing. A
challenge for traditional methods in quality management is to handle high-dimensional and …

Many real-world analytics problems involve two significant challenges: prediction and
optimization. Because of the typically complex nature of each challenge, the standard …

Deep reinforcement learning (DRL) has shown great potential for sequential decision-
making, including early developments in inventory control. Yet, the abundance of choices …

Artificial intelligence (AI) is widely adopted in many areas, but it is still in its infancy in
procurement, despite its potential. To map the state of the art of both research and practice …

The healthcare supply chain lags far behind supply chains in other industries in terms of
performance and the deployment of best practices. Managers could bridge this gap and …

Recently there has been a surge of interest in operations research (OR) and the machine
learning (ML) community in combining prediction algorithms and optimization techniques to …

Food waste reduction and security are the main concerns of agri-food supply chains, as
more than thirty-three percent of global food production is wasted or lost due to …