Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon

15 November 2018

Papers citing "Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon"

50 / 504 papers shown

Title
Subgoal Search For Complex Reasoning Tasks K. Czechowski Tomasz Odrzygó'zd'z Marek Zbysiñski Michał Zawalski Krzysztof Olejnik Yuhuai Wu Lukasz Kuciñski Piotr Milo's ReLM LRM 34 34 0 25 Aug 2021
A New Constructive Heuristic driven by Machine Learning for the Traveling Salesman Problem U. Mele L. Gambardella R. Montemanni 16 13 0 17 Aug 2021
Machine Learning Constructives and Local Searches for the Travelling Salesman Problem Tommaso Vitali U. Mele L. Gambardella R. Montemanni 26 4 0 02 Aug 2021
Learned upper bounds for the Time-Dependent Travelling Salesman Problem Tommaso Adamo G. Ghiani P. Greco E. Guerriero 32 5 0 28 Jul 2021
Accelerating Quadratic Optimization with Reinforcement Learning Jeffrey Ichnowski Paras Jain Bartolomeo Stellato G. Banjac Michael Luo Francesco Borrelli Joseph E. Gonzalez Ion Stoica Ken Goldberg OffRL 19 35 0 22 Jul 2021
Neural Fixed-Point Acceleration for Convex Optimization Shobha Venkataraman Brandon Amos 38 13 0 21 Jul 2021
Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs Nicolas Sonnerat Pengming Wang Ira Ktena Sergey Bartunov Vinod Nair 29 43 0 21 Jul 2021
CoCo: Online Mixed-Integer Control via Supervised Learning Abhishek Cauligi Preston Culbertson Edward Schmerling Mac Schwager Bartolomeo Stellato Marco Pavone 18 41 0 16 Jul 2021
MODRL/D-EL: Multiobjective Deep Reinforcement Learning with Evolutionary Learning for Multiobjective Optimization Yongxin Zhang Jiahai Wang Zizhen Zhang Yalan Zhou 16 21 0 16 Jul 2021
USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization Problems G. Tong 37 5 0 15 Jul 2021
Learning structured approximations of combinatorial optimization problems Axel Parmentier TPM 14 3 0 09 Jul 2021
Reinforced Hybrid Genetic Algorithm for the Traveling Salesman Problem Jiongzhi Zheng Jialun Zhong Menglei Chen Kun He 17 13 0 09 Jul 2021
Deep Learning for Two-Sided Matching S. Ravindranath Zhe Feng Shira Li Jonathan Ma S. Kominers David C. Parkes 23 22 0 07 Jul 2021
Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks Amirhossein Nouranizadeh Mohammadjavad Matinkia Mohammad Rahmati Reza Safabakhsh 19 20 0 03 Jul 2021
Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms Fredrik Präntare Mattias Tiger David Bergstrom Herman Appelgren Fredrik Heintz 9 0 0 01 Jul 2021
Matrix Encoding Networks for Neural Combinatorial Optimization Yeong-Dae Kwon Jinho Choo Iljoo Yoon Minah Park Duwon Park Youngjune Gwon 25 87 0 21 Jun 2021
Goal-Aware Neural SAT Solver Emīls Ozoliņš Kārlis Freivalds Andis Draguns Eliza Gaile Ronalds Zakovskis Sergejs Kozlovics NAI AAML 30 24 0 14 Jun 2021
Contingency-Aware Influence Maximization: A Reinforcement Learning Approach Haipeng Chen Wei Qiu H. Ou Bo An Milind Tambe 14 19 0 13 Jun 2021
Planning Spatial Networks with Monte Carlo Tree Search Victor-Alexandru Darvariu Stephen Hailes Mirco Musolesi 27 7 0 12 Jun 2021
Solving Graph-based Public Good Games with Tree Search and Imitation Learning Victor-Alexandru Darvariu Stephen Hailes Mirco Musolesi 8 1 0 12 Jun 2021
Scalars are universal: Equivariant machine learning, structured like classical physics Soledad Villar D. Hogg Kate Storey-Fisher Weichi Yao Ben Blum-Smith PINN AI4CE 24 130 0 11 Jun 2021
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs Runzhong Wang Zhigang Hua Gan Liu Jiayi Zhang Junchi Yan Feng Qi Shuang Yang Jun Zhou Xiaokang Yang 24 41 0 09 Jun 2021
Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond Maria-Florina Balcan Siddharth Prasad T. Sandholm Ellen Vitercik 9 36 0 08 Jun 2021
Learning Hard Optimization Problems: A Data Generation Perspective James Kotary Ferdinando Fioretto Pascal Van Hentenryck 22 38 0 04 Jun 2021
Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions Mathias Niepert Pasquale Minervini Luca Franceschi 29 81 0 03 Jun 2021
Experiments with graph convolutional networks for solving the vertex $p$ -center problem Elisabeth Gaar Markus Sinnl GNN 28 0 0 01 Jun 2021
Towards Lower Bounds on the Depth of ReLU Neural Networks Christoph Hertrich A. Basu M. D. Summa M. Skutella 34 41 0 31 May 2021
Learning to Select Cuts for Efficient Mixed-Integer Programming Zeren Huang Kerong Wang Furui Liu Hui-Ling Zhen Weinan Zhang M. Yuan Jianye Hao Yong Yu Jun Wang 22 67 0 28 May 2021
Structured Convolutional Kernel Networks for Airline Crew Scheduling Yassine Yaakoubi F. Soumis Simon Lacoste-Julien AI4TS 26 10 0 25 May 2021
A review of approaches to modeling applied vehicle routing problems Konstantin Sidorov Alexander Morozov 16 0 0 23 May 2021
How to effectively use machine learning models to predict the solutions for optimization problems: lessons from loss function M. Abolghasemi B. Abbasi Toktam Babaei S. Z. Hosseinifard AI4CE 13 9 0 14 May 2021
Solve routing problems with a residual edge-graph attention neural network Kun Lei Peng Guo Yi Wang Xiao Wu Wenchao Zhao 32 54 0 06 May 2021
Learning Algorithms for Regenerative Stopping Problems with Applications to Shipping Consolidation in Logistics Kishor Jothimurugan M. Andrews Jeongran Lee Lorenzo Maggi 17 0 0 05 May 2021
Forming Ensembles at Runtime: A Machine Learning Approach T. Bures I. Gerostathopoulos P. Hnetynka J. Pacovský 14 6 0 30 Apr 2021
Constructions in combinatorics via neural networks Adam Zsolt Wagner BDL 32 50 0 29 Apr 2021
DC3: A learning method for optimization with hard constraints P. Donti David Rolnick J. Zico Kolter AI4CE 18 183 0 25 Apr 2021
AutoGL: A Library for Automated Graph Learning Ziwei Zhang Yijian Qin Zeyang Zhang Chaoyu Guan Jie Cai ... Beini Xie Yang Yao Yipeng Zhang Xin Wang Wenwu Zhu 27 30 0 11 Apr 2021
A Reinforcement Learning Environment For Job-Shop Scheduling Pierre Tassel M. Gebser Konstantin Schekotihin OffRL 22 49 0 08 Apr 2021
Ecole: A Library for Learning Inside MILP Solvers Antoine Prouvost Justin Dumouchelle Maxime Gasse Didier Chételat Andrea Lodi 11 4 0 06 Apr 2021
SOLO: Search Online, Learn Offline for Combinatorial Optimization Problems J. Oren Chana Ross Maksym Lefarov Felix Richter Ayal Taitler Zohar Feldman Christian Daniel Dotan Di Castro OffRL 19 22 0 04 Apr 2021
Learning to Optimize: A Primer and A Benchmark Tianlong Chen Xiaohan Chen Wuyang Chen Howard Heaton Jialin Liu Zhangyang Wang W. Yin 43 225 0 23 Mar 2021
Set-to-Sequence Methods in Machine Learning: a Review Mateusz Jurewicz Leon Derczynski BDL 27 9 0 17 Mar 2021
A Two-stage Framework and Reinforcement Learning-based Optimization Algorithms for Complex Scheduling Problems Yongming He Guohua Wu Yingwu Chen Witold Pedrycz 11 8 0 10 Mar 2021
Self-play Learning Strategies for Resource Assignment in Open-RAN Networks Xiaoyang Wang Jonathan D. Thomas Robert Piechocki S. Kapoor Raúl Santos-Rodríguez Arjun Parekh 24 24 0 03 Mar 2021
Fast Approximate Solutions using Reinforcement Learning for Dynamic Capacitated Vehicle Routing with Time Windows Nazneen N. Sultana Vinita Baniwal Ansuma Basumatary P. Mittal Supratim Ghosh H. Khadilkar 20 10 0 24 Feb 2021
Analytics and Machine Learning in Vehicle Routing Research Ruibin Bai Xinan Chen Zhi-Long Chen Tianxiang Cui Shuhui Gong ... Zhengyong Lu Jianfeng Ren Paul Weng Ning Xue Huayan Zhang 16 77 0 19 Feb 2021
Combinatorial optimization and reasoning with graph neural networks Quentin Cappart Didier Chételat Elias Boutros Khalil Andrea Lodi Christopher Morris Petar Velickovic AI4CE 32 347 0 18 Feb 2021
SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning Félix Chalumeau Ilan Coulon Quentin Cappart Louis-Martin Rousseau 36 21 0 18 Feb 2021
Planning and Learning Using Adaptive Entropy Tree Search Piotr Kozakowski Mikolaj Pacek Piotr Milo's 19 2 0 12 Feb 2021
ReLU Neural Networks of Polynomial Size for Exact Maximum Flow Computation Christoph Hertrich Leon Sering 37 10 0 12 Feb 2021