This special issue in Annals of Operations Research seeks original research advancing theoretical foundations, modeling approaches, and algorithms for optimization and decision making under uncertainty. The focus encompasses mathematical optimization, stochastic and robust optimization, game theory, and learning-based optimization techniques, welcoming contributions that develop new models, analytical results, and computational methodologies.
The special issue is organized alongside the International Conference on Operations Research: Theory, Applications and Emerging Technologies (ICORSI 2026) at Indian Institute of Technology Delhi, though participation is not required. It welcomes all researchers working on recent advances in optimization theory and methods for decision making under uncertainty.