With the relentless increase in computing power and the ubiquitous availability of data in many industries, the fields of simulation optimization and artificial intelligence have emerged at the scientific and engineering forefront in their societal impact, manifested in the pervasiveness of technologies such as large language models, chatbots, digital twins, and agent-based systems. We examine cross-fertilization between simulation optimization and artificial intelligence, with a particular focus on reinforcement learning, highlighting research that has been mutually beneficial. This work presents examples of the synergies between the fields, followed by real-world applications and case studies, including some futurist and forward-looking concepts.
Yijie Peng (Peking University), Chun-Hung Chen (George Mason University, and Michael C. Fu (University of Maryland)
Foundations and Trends in Optimization