Abdel Lisser, CentraleSupélec

Jia Liu, Xi'an Jiaotong University

Francesca Maggioni, University of Bergamo

S. K. Neogy, Indian Statistical Institute

Vikas Vikram Singh, Indian Institute of Technology Delhi

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.

Appel publié par Annals of Operations Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Mathematical programming
• Convex, nonconvex, and mixed-integer optimization
• Stochastic, robust, and distributionally robust optimization
• Chance-constrained optimization
• Variational inequalities and equilibrium problems
• Game theory and multi-agent optimization
• Markov decision processes and stochastic games
• Reinforcement learning for sequential decision making
• Online and data-driven optimization
• Optimization under risk measures
• Bayesian optimization
• Black-box optimization

Timeline

• March 31, 2028: Submission deadline