Adaptive solution prediction for combinatorial optimization

Y Shen, Y Sun, X Li, A Eberhard, A Ernst - European Journal of Operational …, 2023 - Elsevier
This paper aims to predict optimal solutions for combinatorial optimization problems (COPs)
via machine learning (ML). To find high-quality solutions efficiently, existing work uses a ML …

Saving computational budget in Bayesian network-based evolutionary algorithms

M Scoczynski, M Delgado, R Lüders, D Oliva… - Natural Computing, 2021 - Springer
During the evolutionary process, algorithms based on probability distributions for generating
new individuals suffer from computational burden due to the intensive computation of …

[PDF][PDF] Multi-shot Solution Prediction for Combinatorial Optimization

Y Shena, XL Yuan Sunb, A Eberhardc… - arxiv preprint arxiv …, 2022 - academia.edu
This paper aims to predict optimal solutions for combinatorial optimization problems (COPs)
via machine learning (ML). To find high-quality solutions efficiently, existing methods use a …

[PDF][PDF] Enhancing combinatorial optimization through solution prediction using machine learning

S Yunzhuang - 2023 - research-repository.rmit.edu.au
An unceasing pursuit in large-scale combinatorial optimization is to find feasible solutions
with improved quality and speed. Modern MIP solvers have incorporated a wide array of …