3 papers
cs.LG2026
StarOR: Synergizing Tree Search and Test-Time Reinforcement Learning for Optimization Modeling
Jiajun Li, Yu Ding, Shisi Guan +2
Optimization modeling is inherently hierarchical, requiring a precise sequence of symbolic commitments. Traditional learning-based automated optimization modeling methods improve m…
cs.LG2026
Constraint Matters: Multi-Modal Representation for Reducing Mixed-Integer Linear programming
Jiajun Li, Yixuan Li, Ran Hou +8
Model reduction, which aims to learn a simpler model of the original mixed integer linear programming (MILP), can solve large-scale MILP problems much faster. Most existing model r…
cs.AI2025
A Survey of Optimization Modeling Meets LLMs: Progress and Future Directions
Ziyang Xiao, Jingrong Xie, Lilin Xu +15
By virtue of its great utility in solving real-world problems, optimization modeling has been widely employed for optimal decision-making across various sectors, but it requires su…