Back in 2001, Bixby et al.(The Sharpest Cut: The Impact of Manfred Padberg and His Work,
pp. 309–325, 2004) provided an analysis of the performance impact of the main mixed …

The latest two-stage optimization framework based on graph neural network (GNN) and
large neighborhood search (LNS) is the most popular framework in solving large-scale …

In modern MIP solvers, primal heuristics play a key role in finding high-quality solutions.
However, classical performance measures reflect the impact of primal heuristics on the …

In response to the needs of researchers for access to challenging mixed integer programs,
Bixby et al. 1] created MIPLIB, an electronically available library of both pure and mixed …

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 …

The branch-and-bound procedure for solving mixed integer programming (MIP) problems
using linear programming relaxations has been used with great success for decades. Over …

We present a flexible framework for general mixed-integer nonlinear programming (MINLP),
called Minotaur, that enables both algorithm exploration and structure exploitation without …

In this paper we investigate the effects of replacing the objective function of a 0-1 mixed-
integer convex program (MIP) with a “proximity” one, with the aim of using a black-box solver …

Even with state-of-the-art hardware and software, mixed integer programs can require hours,
or even days, of run time and are not guaranteed to yield an optimal (or near-optimal, or …

Mixed integer programming (MIP) has become one of the most important techniques in
Operations Research and Discrete Optimization. SCIP (Solving Constraint Integer …