Learning to Compare Nodes in Branch and Bound with Graph Neural Networks

30 October 2022

Papers citing "Learning to Compare Nodes in Branch and Bound with Graph Neural Networks"

7 / 7 papers shown

Title
Towards Foundation Models for Mixed Integer Linear Programming Sirui Li Janardhan Kulkarni Ishai Menache Cathy Wu Beibin Li 170 15 0 24 Feb 2025
Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop Scheduling Sirui Li Wenbin Ouyang Yining Ma Cathy Wu 158 1 0 18 Feb 2025
Towards graph neural networks for provably solving convex optimization problems Chendi Qian Christopher Morris 132 2 0 04 Feb 2025
Rethinking the Capacity of Graph Neural Networks for Branching Strategy Ziang Chen Jialin Liu Xiaohan Chen Xinshang Wang Wotao Yin 199 6 0 11 Feb 2024
Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning Yufei Kuang Xijun Li Jie Wang Fangzhou Zhu Meng Lu Zhihai Wang Jianguo Zeng Houqiang Li Yongdong Zhang Feng Wu 113 5 0 18 Oct 2023
Reinforcement Learning for Node Selection in Branch-and-Bound Alexander Mattick Christopher Mutschler 88 2 0 29 Sep 2023
Combinatorial optimization and reasoning with graph neural networks Quentin Cappart Didier Chételat Elias Boutros Khalil Andrea Lodi Christopher Morris Petar Velickovic AI4CE 195 382 0 18 Feb 2021