7 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…
Distributed Parallel Structure-Aware Presolving for Arrowhead Linear Programs
Nils-Christian Kempke, Stephen J Maher, Daniel Rehfeldt +3
We present a structure-aware parallel presolve framework specialized to arrowhead linear programs (AHLPs) and designed for high-performance computing (HPC) environments, integrated…
GPU accelerated variant of Schroeppel-Shamir's algorithm for solving the market split problem
Nils-Christian Kempke, Thorsten Koch
The market split problem (MSP), introduced by Cornuejols and Dawande (1998), is a challenging binary optimization problem that performs poorly on state-of-the-art linear programmin…
Fix-and-Propagate Heuristics Using Low-Precision First-Order LP Solutions for Large-Scale Mixed-Integer Linear Optimization
Nils-Christian Kempke, Thorsten Koch
We investigate the use of low-precision first-order methods (FOMs) within a fix-and-propagate (FP) framework for solving mixed-integer programming problems (MIPs). We employ GPU-ac…
Developing heuristic solution techniques for large-scale unit commitment models
Nils-Christian Kempke, Tim Kunt, Bassel Katamish +4
Shifting towards renewable energy sources and reducing carbon emissions necessitate sophisticated energy system planning, optimization, and extension. Energy systems optimization m…
A Massively Parallel Interior-Point Method for Arrowhead Linear Programs with Local Linking Structure
Nils-Christian Kempke, Daniel Rehfeldt, Thorsten Koch
In practice, non-specialized interior point algorithms often cannot utilize the massively parallel compute resources offered by modern many- and multi-core compute platforms. Howev…