Mixed Integer Linear Program

Mixed Integer Linear Programs (MILPs) are mathematical optimization problems combining continuous and discrete variables, aiming to find optimal solutions within constraints. Current research focuses on improving solution efficiency through advanced algorithms like branch-and-cut, Lagrangian relaxation, and novel approaches leveraging machine learning, including deep learning models for predicting optimal parameters and reinforcement learning for improved branching strategies. These advancements are significantly impacting various fields, from autonomous systems and logistics (e.g., optimizing routing) to accelerating the performance of existing MILP solvers and enabling the solution of larger, more complex problems.