Towards foundation models for mixed integer linear programming

S Li, J Kulkarni, I Menache, C Wu, B Li - arXiv preprint arXiv:2410.08288, 2024 - arxiv.org
Mixed Integer Linear Programming (MILP) is essential for modeling complex decision-
making problems but faces challenges in computational tractability and requires expert …

Fast and Interpretable Mixed-Integer Linear Program Solving by Learning Model Reduction

Y Li, C Chen, J Li, J Duan, X Han, T Zhong… - arXiv preprint arXiv …, 2024 - arxiv.org
By exploiting the correlation between the structure and the solution of Mixed-Integer Linear
Programming (MILP), Machine Learning (ML) has become a promising method for solving …

[HTML][HTML] Hyperparameter optimization: Classics, acceleration, online, multi-objective, and tools

JM Tan, H Liao, W Liu, C Fan, J Huang… - Mathematical …, 2024 - aimspress.com
Hyperparameter optimization (HPO) has been well-developed and evolved into a well-
established research topic over the decades. With the success and wide application of deep …

The Use of Machine Learning and AI to Improve Computational Performance in Large-Scale Optimization and Time Series Applications

M Ye - 2024 - search.proquest.com
The three essays in my dissertation proposal examine the use of machine learning and
artificial intelligence (ML/AI) for performance improvement in large-scale combinatorial …