87 citations · 88 across the 10 of their papers we have counts for
10 papers
CHAP: A Hybrid GPU-CPU Heuristic for MIP
Gennesaret Kharistio Tjusila, Alexander Hoen, Nils-Christian Kempke +5
We present CHAP (Coordinating Heuristics Across Platforms) a GPU-CPU-hybrid primal heuristic framework for mixed-integer programming. CHAP adopts a portfolio approach where it coor…
Out-of-the-Box Global Optimization for Packing Problems: New Models and Improved Solutions
Timo Berthold, Dominik Kamp, Gioni Mexi +2
Recent LLM-driven discoveries have renewed interest in geometric packing problems. In this paper, we study several classes of such packing problems through the lens of modern globa…
Improving Conflict Analysis in MIP Solvers by Pseudo-Boolean Reasoning
Gioni Mexi, Timo Berthold, Ambros Gleixner +1
Conflict analysis has been successfully generalized from Boolean satisfiability (SAT) solving to mixed integer programming (MIP) solvers, but although MIP solvers operate with gene…
A Context-Aware Cutting Plane Selection Algorithm for Mixed-Integer Programming
Mark Turner, Timo Berthold, Mathieu Besançon
The current cut selection algorithm used in mixed-integer programming solvers has remained largely unchanged since its creation. In this paper, we propose a set of new cut scoring…
Branching via Cutting Plane Selection: Improving Hybrid Branching
Mark Turner, Timo Berthold, Mathieu Besançon +1
Cutting planes and branching are two of the most important algorithms for solving mixed-integer linear programs. For both algorithms, disjunctions play an important role, being use…
Cutting Plane Selection with Analytic Centers and Multiregression
Mark Turner, Timo Berthold, Mathieu Besançon +1
Cutting planes are a crucial component of state-of-the-art mixed-integer programming solvers, with the choice of which subset of cuts to add being vital for solver performance. We…
Progress in Mathematical Programming Solvers from 2001 to 2020
Thorsten Koch, Timo Berthold, Jaap Pedersen +1
This study investigates the progress made in LP and MILP solver performance during the last two decades by comparing the solver software from the beginning of the millennium with t…
A Status Report on Conflict Analysis in Mixed Integer Nonlinear Programming
Jakob Witzig, Timo Berthold, Stefan Heinz
Mixed integer nonlinear programs (MINLPs) are arguably among the hardest optimization problems, with a wide range of applications. MINLP solvers that are based on linear relaxation…
Local Rapid Learning for Integer Programs
Timo Berthold, Peter J. Stuckey, Jakob Witzig
Conflict learning algorithms are an important component of modern MIP and CP solvers. But strong conflict information is typically gained by depth-first search. While this is the n…
Experiments with Conflict Analysis in Mixed Integer Programming
Jakob Witzig, Timo Berthold, Stefan Heinz
The analysis of infeasible subproblems plays an import role in solving mixed integer programs (MIPs) and is implemented in most major MIP solvers. There are two fundamentally diffe…