Hybrid Models for Learning to Branch

26 June 2020

Papers citing "Hybrid Models for Learning to Branch"

50 / 69 papers shown

Title
PROPEL: Supervised and Reinforcement Learning for Large-Scale Supply Chain Planning Vahid Eghbal Akhlaghi Reza Zandehshahvar Pascal Van Hentenryck 31 0 0 10 Apr 2025
Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming Haoyang Liu Jie Wang Zijie Geng Xijun Li Yuxuan Zong Fangzhou Zhu Jianye Hao Feng Wu 66 3 0 03 Mar 2025
Towards Foundation Models for Mixed Integer Linear Programming Sirui Li Janardhan Kulkarni Ishai Menache Cathy Wu Beibin Li 57 4 0 24 Feb 2025
Robotic warehousing operations: a learn-then-optimize approach to large-scale neighborhood search Cynthia Barnhart Alexandre Jacquillat Alexandria Schmid 29 0 0 29 Aug 2024
Learning to Remove Cuts in Integer Linear Programming Pol Puigdemont Stratis Skoulakis Grigorios G. Chrysos V. Cevher 32 1 0 26 Jun 2024
Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs Ziang Chen Xiaohan Chen Jialin Liu Xinshang Wang Wotao Yin 45 4 0 09 Jun 2024
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming Bingheng Li Linxin Yang Yupeng Chen Senmiao Wang Qian Chen ... Yao Ma Akang Wang Tian Ding Jiliang Tang Ruoyu Sun AI4CE 37 7 0 04 Jun 2024
Metric Learning to Accelerate Convergence of Operator Splitting Methods for Differentiable Parametric Programming Ethan King James Kotary Ferdinando Fioretto Ján Drgoňa 32 2 0 01 Apr 2024
Machina Economicus: A New Paradigm for Prosumers in the Energy Internet of Smart Cities Luyang Hou Jun Yan Yuankai Wu Chun Wang Tie Qiu 24 0 0 28 Feb 2024
Rethinking the Capacity of Graph Neural Networks for Branching Strategy Ziang Chen Jialin Liu Xiaohan Chen Xinshang Wang Wotao Yin 53 3 0 11 Feb 2024
Machine Learning Augmented Branch and Bound for Mixed Integer Linear Programming Lara Scavuzzo K. Aardal Andrea Lodi Neil Yorke-Smith 51 19 0 08 Feb 2024
CAMBranch: Contrastive Learning with Augmented MILPs for Branching Jiacheng Lin Meng Xu Zhihua Xiong Huangang Wang 22 3 0 06 Feb 2024
Learning to Stop Cut Generation for Efficient Mixed-Integer Linear Programming Haotian Ling Zhihai Wang Jie Wang 47 5 0 31 Jan 2024
Machine Learning Insides OptVerse AI Solver: Design Principles and Applications Xijun Li Fangzhou Zhu Hui-Ling Zhen Weilin Luo Meng Lu ... Jia Zeng M. Yuan Jianye Hao Jun Yao Kun Mao 38 2 0 11 Jan 2024
Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process Zhenan Fan Bissan Ghaddar Xinglu Wang Linzi Xing Yong Zhang Zirui Zhou AI4CE 53 11 0 06 Jan 2024
NN-Steiner: A Mixed Neural-algorithmic Approach for the Rectilinear Steiner Minimum Tree Problem Andrew B. Kahng Robert Nerem Yusu Wang Chien-Yi Yang 22 5 0 17 Dec 2023
Solve Large-scale Unit Commitment Problems by Physics-informed Graph Learning Jingtao Qin Nanpeng Yu 11 2 0 26 Nov 2023
Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks M. Seyfi Amin Banitalebi-Dehkordi Zirui Zhou Yong Zhang 49 4 0 23 Nov 2023
Learning to Configure Separators in Branch-and-Cut Sirui Li Wenbin Ouyang Max B. Paulus Cathy Wu 24 8 0 08 Nov 2023
Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation Haoyang Liu Yufei Kuang Jie Wang Xijun Li Yongdong Zhang Feng Wu AAML 54 7 0 22 Oct 2023
Exploring the Power of Graph Neural Networks in Solving Linear Optimization Problems Chendi Qian Didier Chételat Christopher Morris 52 17 0 16 Oct 2023
On Statistical Learning of Branch and Bound for Vehicle Routing Optimization Andrew Naguib Waleed A. Yousef Issa Traoré Mohammed Mamun 18 0 0 15 Oct 2023
Taking the human out of decomposition-based optimization via artificial intelligence: Part II. Learning to initialize Ilias Mitrai P. Daoutidis AI4CE 24 5 0 10 Oct 2023
Taking the human out of decomposition-based optimization via artificial intelligence: Part I. Learning when to decompose Ilias Mitrai P. Daoutidis 25 4 0 10 Oct 2023
Physics-Informed Graph Neural Network for Dynamic Reconfiguration of Power Systems Jules Authier R. Haider Anuradha M. Annaswamy Florian Dorfler AI4CE PINN 25 4 0 01 Oct 2023
Are Graph Neural Networks Optimal Approximation Algorithms? Morris Yau Eric Lu Nikolaos Karalias Jessica Xu Stefanie Jegelka 28 1 0 01 Oct 2023
Learning to Branch in Combinatorial Optimization with Graph Pointer Networks Rui Wang Zhiming Zhou Tao Zhang Ling Wang Xin Xu Xiangke Liao Kaiwen Li 50 2 0 04 Jul 2023
A Neural Separation Algorithm for the Rounded Capacity Inequalities Hyeon-Seob Kim Jinkyoo Park C. Kwon 49 6 0 29 Jun 2023
TreeDQN: Learning to minimize Branch-and-Bound tree Dmitry Sorokin A. Kostin 16 1 0 09 Jun 2023
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets Dinghuai Zhang H. Dai Nikolay Malkin Aaron Courville Yoshua Bengio L. Pan 28 36 0 26 May 2023
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning Taoan Huang Aaron Ferber Yuandong Tian B. Dilkina Benoit Steiner 47 22 0 03 Feb 2023
Learning To Dive In Branch And Bound Max B. Paulus Andreas Krause 29 4 0 24 Jan 2023
Learning to Compare Nodes in Branch and Bound with Graph Neural Networks Abdel Ghani Labassi Didier Chételat Andrea Lodi 24 31 0 30 Oct 2022
On Representing Mixed-Integer Linear Programs by Graph Neural Networks Ziang Chen Jialin Liu Xinshang Wang Jian Lu W. Yin AI4CE 34 17 0 19 Oct 2022
On Representing Linear Programs by Graph Neural Networks Ziang Chen Jialin Liu Xinshang Wang Jian Lu W. Yin AI4CE 60 31 0 25 Sep 2022
Lifelong Learning for Neural powered Mixed Integer Programming S. Manchanda Sayan Ranu CLL 33 1 0 24 Aug 2022
Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning Zeren Huang Wenhao Chen Weinan Zhang Chuhan Shi Furui Liu Hui-Ling Zhen M. Yuan Jianye Hao Yong Yu Jun Wang OffRL 34 2 0 26 Jul 2022
Learning to Accelerate Approximate Methods for Solving Integer Programming via Early Fixing Longkang Li Baoyuan Wu 21 3 0 05 Jul 2022
Lookback for Learning to Branch Prateek Gupta Elias Boutros Khalil Didier Chételat Maxime Gasse Yoshua Bengio Andrea Lodi M. P. Kumar 12 28 0 30 Jun 2022
Grid-SiPhyR: An end-to-end learning to optimize framework for combinatorial problems in power systems R. Haider Anuradha M. Annaswamy 31 2 0 11 Jun 2022
Reinforcement Learning for Branch-and-Bound Optimisation using Retrospective Trajectories Christopher W. F. Parsonson Alexandre Laterre Thomas D. Barrett 25 19 0 28 May 2022
MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers Elias Boutros Khalil Christopher Morris Andrea Lodi AI4CE 33 48 0 27 May 2022
Learning to Solve Combinatorial Graph Partitioning Problems via Efficient Exploration Thomas D. Barrett Christopher W. F. Parsonson Alexandre Laterre 29 10 0 27 May 2022
DOGE-Train: Discrete Optimization on GPU with End-to-end Training Ahmed Abbas Paul Swoboda 38 6 0 23 May 2022
Learning to branch with Tree MDPs Lara Scavuzzo F. Chen Didier Chételat Maxime Gasse Andrea Lodi Neil Yorke-Smith K. Aardal AI4CE 37 51 0 23 May 2022
High Performance of Gradient Boosting in Binding Affinity Prediction Dmitrii Gavrilev Nurlybek Amangeldiuly Sergei Ivanov Evgeny Burnaev AI4CE 33 2 0 14 May 2022
Learning for Spatial Branching: An Algorithm Selection Approach Bissan Ghaddar Ignacio Gómez-Casares Julio González-Díaz Brais González-Rodríguez Beatriz Pateiro-López Sofía Rodríguez-Ballesteros 29 12 0 22 Apr 2022
A Survey for Solving Mixed Integer Programming via Machine Learning Jiayi Zhang Chang-rui Liu Junchi Yan Xijun Li Hui-Ling Zhen M. Yuan AI4CE 40 72 0 06 Mar 2022
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights Maxime Gasse Quentin Cappart J. Charfreitag Laurent Charlin Didier Chételat ... He Minggui Hao Hao Zhang Zhiyu An Zhiwu M. Kun 30 30 0 04 Mar 2022
Neural Simulated Annealing Alvaro H. C. Correia Daniel E. Worrall Roberto Bondesan 19 7 0 04 Mar 2022