Applied Machine Learning in Operations Management

Abstract

The field of operations management has witnessed a fast-growing trend of data analytics in recent years. In particular, spurred by the increasing availability of data and methodological advancement in machine learning, a large body of recent literature in this field takes advantage of machine learning techniques for analyzing how firms should operate. We review applications of different machine learning methods, including supervised learning, unsupervised learning, and reinforcement learning, in various areas of operations management. We highlight how both supervised and unsupervised learning shape operations management research in both descriptive and prescriptive analyses. We also emphasize how different variants of reinforcement learning are applied in diverse operational decision problems. We then identify several exciting future directions at the intersection of machine learning and operations management.

Keywords: Machine Learning, Supervised Learning, Unsupervised Learning, Reinforcement Learning, Operations Management, Data Analytics, Healthcare, Revenue Management, Supply Chain Management