Branch-and-bound is a widely used method in combinatorial optimization, including mixed
integer programming, structured prediction and MAP inference. While most work has been …

Abstract Branch and Bound (B&B) is the exact tree search method typically used to solve
Mixed-Integer Linear Programming problems (MILPs). Learning branching policies for MILP …

The design of strategies for branching in Mixed Integer Programming (MIP) is guided by
cycles of parameter tuning and offline experimentation on an extremely heterogeneous …

Abstract “Primal heuristics” are a key contributor to the improved performance of exact
branch-and-bound solvers for combinatorial optimization and integer programming. Perhaps …

Abstract A recent Graph Neural Network (GNN) approach for learning to branch has been
shown to successfully reduce the running time of branch-and-bound algorithms for Mixed …

This paper surveys learning techniques to deal with the two most crucial decisions in the
branch-and-bound algorithm for Mixed-Integer Linear Programming, namely variable and …

Primal heuristics play a crucial role in exact solvers for Mixed Integer Programming (MIP).
While solvers are guaranteed to find optimal solutions given sufficient time, real-world …

State-of-the-art Mixed Integer Linear Programming (MILP) solvers combine systematic tree
search with a plethora of hard-coded heuristics, such as branching rules. While approaches …

Mixed integer linear programs are commonly solved by Branch and Bound algorithms. A key
factor of the efficiency of the most successful commercial solvers is their fine-tuned …

Finding high-quality solutions to mixed-integer linear programming problems (MILPs) is of
great importance for many practical applications. In this respect, the refinement heuristic …