The use of Generative Artificial Intelligence (GenAI) in operations research: review and future research agenda
Year: 2025
Type: article
Study design: Systematic Review
Abstract: The emergence of Generative Artificial Intelligence (GenAI) represents a significant advancement in computational capabilities, offering transformative potential for the field of Operations Research (OR). This study explores the role of GenAI in OR by conducting a systematic literature review. Following a careful analysis of the collected works, the reviewed papers are classified into two main categories based on the nature of their contributions: (1) application papers and (2) review and position papers. The latter provide a conceptual overview of GenAI’s broader implications for OR, while the application papers are organized into a taxonomy encompassing three core dimensions: (1) GenAI for mathematical programming and optimization, (2) GenAI for stochastic systems, and (3) GenAI for simulation, strategic analysis, game theory, and risk management. Drawing insights from both conceptual and empirical studies, this review identifies cross-cutting themes and outlines a future research agenda to guide continued exploration at the intersection of GenAI and OR.
Authors: Qin Zhou, Jiuh-Biing Sheu
Institutions: University of Southampton, National Taiwan University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4414279533