The SCIP Optimization Suite provides a collection of software packages for mathematical
optimization centered around the constraint integer programming frame-work SCIP. This …

Cutting planes are crucial in solving mixed integer linear programs (MILP) as they facilitate
bound improvements on the optimal solution. Modern MILP solvers rely on a variety of …

Cutting planes (cuts) are important for solving mixed-integer linear programs (MILPs), which
formulate a wide range of important real-world applications. Cut selection--which aims to …

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 …

We present Ecole, a new library to simplify machine learning research for combinatorial
optimization. Ecole exposes several key decision tasks arising in general-purpose …

The SCIP Optimization Suite provides a collection of software packages for mathematical
optimization, centered around the constraint integer programming (CIP) framework SCIP …

Abstract Large Neighborhood Search (LNS) heuristics are among the most powerful but also
most expensive heuristics for mixed integer programs (MIP). Ideally, a solver adaptively …

Abstract Mixed Integer Linear Programming (MILP) is a pillar of mathematical optimization
that offers a powerful modeling language for a wide range of applications. The main engine …

In an era of digital ubiquity, efficient resource management and decision-making are
paramount across numerous industries. To this end, we present a comprehensive study on …

The winner determination problem of a combinatorial auction can be modeled as mixed-
integer linear programming, and is a popular benchmark to evaluate modern solvers …