Safia Kedad-Sidhoum

Planning in Branch-and-Bound: Model-Based Reinforcement Learning for Exact Combinatorial Optimization

Mixed-Integer Linear Programming (MILP) lies at the core of many real-world combinatorial optimization (CO) problems, traditionally solved by branch-and-bound (B&B). A key driver influencing B&B solvers efficiency is the variable selection heuristic that guides branching decisions. Looking to move b