Special issue on “Integration of Operations Research with Digital Twins and AI”

The International Transactions in Operational Research (ITOR), the flagship journal published by the International Federation of Operational Research Societies, will publish a special issue dedicated to the Integration of Operations Research with Digital Twins and AI.Digital twins (DT) and artificial intelligence (AI) are transforming operations research (OR).OR methods depend on the collection, processing, reasoning, and integration of data.While some of these tasks still require human expertise, many have become automated or can be managed by AI, such as data-driven and language-based model development.Historically, limitations in data availability and certainty led to the creation of OR methods based on probabilistic predictions.With DT and AI, these constraints are eased, prompting critical questions about the continued relevance and effectiveness of traditional optimization and simulation techniques for modern, AIdriven operations and supply chains.At the same time, the integration of OR with agentic AI ecosystems is opening new opportunities, which this special issue seeks to explore, together with potential challenges.DT and AI fundamentally redefine what constitutes a "model."Models can become dynamic, able to reconfigure their structure and functionality in response to data, AI-driven insights, and collaboration between humans and AI.This shift moves the focus from purely algorithmic engineering to creative engagement with AI assistants, evaluating agent interactions, validating optimization suggestions, and testing scenarios using real-time or frequently updated data under various uncertainties.Instead of optimizing isolated models, agentic AI and DT enable coordinated decision systems built on human-AI collaboration.Integrating with DT and AI is essential for OR to remain relevant in a data-and AI-centric landscape.Traditional optimization methods often overlook the needs of end users, who face complex, unstructured problems with multiple objectives and uncertainties.Users expect a flexible environment that enables real-time exploration of alternatives, scenarios, and uncertainties, and that allows