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 / 501 papers shown

Title
A learning-based solution approach to the application placement problem in mobile edge computing under uncertainty T. Hejazi Zahra Ghadimkhani Arezoo Borji 21 0 0 17 Mar 2024
Leveraging Constraint Programming in a Deep Learning Approach for Dynamically Solving the Flexible Job-Shop Scheduling Problem Imanol Echeverria M. Murua Roberto Santana 34 5 0 14 Mar 2024
A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms Raffaele Marino L. Buffoni Bogdan Zavalnij GNN 40 5 0 13 Mar 2024
Learning-Enhanced Neighborhood Selection for the Vehicle Routing Problem with Time Windows Willem Feijen Guido Schäfer Koen Dekker Seppo Pieterse 16 1 0 13 Mar 2024
Ant Colony Sampling with GFlowNets for Combinatorial Optimization Minsu Kim Sanghyeok Choi Hyeon-Seob Kim Jiwoo Son Jinkyoo Park Yoshua Bengio 43 23 0 11 Mar 2024
Towards a Generic Representation of Combinatorial Problems for Learning-Based Approaches Léo Boisvert Hélene Verhaeghe Quentin Cappart 24 5 0 09 Mar 2024
Learning to Deliver: a Foundation Model for the Montreal Capacitated Vehicle Routing Problem Samuel J. K. Chin Matthias Winkenbach Akash Srivastava 29 0 0 28 Feb 2024
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints Lingkai Kong Yuanqi Du Wenhao Mu Kirill Neklyudov Valentin De Bortol ... D. Wu Aaron Ferber Yi Ma Carla P. Gomes Chao Zhang 27 10 0 28 Feb 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 14 0 0 28 Feb 2024
A Neural-Evolutionary Algorithm for Autonomous Transit Network Design Andrew Holliday Gregory Dudek 59 0 0 27 Feb 2024
Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization Fei Liu Xi Lin Zhenkun Wang Qingfu Zhang Xialiang Tong Mingxuan Yuan 29 20 0 23 Feb 2024
Geometry-Informed Neural Networks Arturs Berzins Andreas Radler Sebastian Sanokowski Sepp Hochreiter Johannes Brandstetter GAN AI4CE 38 1 0 21 Feb 2024
Deep learning-driven scheduling algorithm for a single machine problem minimizing the total tardiness Michal Bouška P. Šůcha A. Novák Z. Hanzálek 38 9 0 19 Feb 2024
Large Scale Constrained Clustering With Reinforcement Learning Benedikt Schesch Marco Caserta 26 0 0 15 Feb 2024
Feed-Forward Neural Networks as a Mixed-Integer Program Navid Aftabi Nima Moradi Fatemeh Mahroo 17 2 0 09 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 17 3 0 06 Feb 2024
torchmSAT: A GPU-Accelerated Approximation To The Maximum Satisfiability Problem Abdelrahman I. Hosny Sherief Reda 13 1 0 06 Feb 2024
A Reinforcement Learning Approach for Dynamic Rebalancing in Bike-Sharing System Jiaqi Liang Sanjay Dominik Jena Defeng Liu Andrea Lodi 45 1 0 05 Feb 2024
Dual Lagrangian Learning for Conic Optimization Mathieu Tanneau Pascal Van Hentenryck 24 4 0 05 Feb 2024
Genetic-based Constraint Programming for Resource Constrained Job Scheduling Su Nguyen D. Thiruvady Yuan Sun Mengjie Zhang 17 1 0 01 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
Self-Labeling the Job Shop Scheduling Problem Andrea Corsini Angelo Porrello Simone Calderara Mauro DellÁmico SSL 11 14 0 22 Jan 2024
Learning-assisted Stochastic Capacity Expansion Planning: A Bayesian Optimization Approach Aron Brenner Rahman Khorramfar D. Mallapragada Saurabh Amin 14 0 0 19 Jan 2024
Deep learning enhanced mixed integer optimization: Learning to reduce model dimensionality Niki Triantafyllou M. Papathanasiou 31 4 0 17 Jan 2024
Distance-aware Attention Reshaping: Enhance Generalization of Neural Solver for Large-scale Vehicle Routing Problems Yang Wang Ya-Hui Jia Wei-neng Chen Yi Mei 36 9 0 13 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 32 2 0 11 Jan 2024
Boosting Column Generation with Graph Neural Networks for Joint Rider Trip Planning and Crew Shift Scheduling Jiawei Lu Tinghan Ye Wenbo Chen Pascal Van Hentenryck AI4TS 35 0 0 08 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
Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model Fei Liu Xialiang Tong Mingxuan Yuan Xi Lin Fu Luo Zhenkun Wang Zhichao Lu Qingfu Zhang VLM 40 55 0 04 Jan 2024
Swap-based Deep Reinforcement Learning for Facility Location Problems in Networks Wenxuan Guo Yanyan Xu Yaohui Jin 19 1 0 25 Dec 2023
Learning Lagrangian Multipliers for the Travelling Salesman Problem Augustin Parjadis Quentin Cappart B. Dilkina Aaron Ferber Louis-Martin Rousseau 37 1 0 22 Dec 2023
A Reinforcement-Learning-Based Multiple-Column Selection Strategy for Column Generation Haofeng Yuan Lichang Fang Shiji Song 38 4 0 21 Dec 2023
NN-Steiner: A Mixed Neural-algorithmic Approach for the Rectilinear Steiner Minimum Tree Problem Andrew B. Kahng Robert Nerem Yusu Wang Chien-Yi Yang 17 5 0 17 Dec 2023
Multi-Objective Reinforcement Learning-based Approach for Pressurized Water Reactor Optimization Paul Seurin K. Shirvan 24 9 0 15 Dec 2023
Symmetry Breaking and Equivariant Neural Networks Sekouba Kaba Siamak Ravanbakhsh 38 12 0 14 Dec 2023
Machine Learning for the Multi-Dimensional Bin Packing Problem: Literature Review and Empirical Evaluation Wenjie Wu Changjun Fan Jin-Yu Huang Zhong Liu Junchi Yan 28 0 0 13 Dec 2023
gcDLSeg: Integrating Graph-cut into Deep Learning for Binary Semantic Segmentation Hui Xie Weiyu Xu Ya Xing Wang John Buatti Xiaodong Wu SSeg 23 1 0 07 Dec 2023
Approximating Solutions to the Knapsack Problem using the Lagrangian Dual Framework Mitchell Keegan Mahdi Abolghasemi 56 0 0 06 Dec 2023
Algorithm Evolution Using Large Language Model Fei Liu Xialiang Tong Mingxuan Yuan Qingfu Zhang 24 39 0 26 Nov 2023
Variational Annealing on Graphs for Combinatorial Optimization Sebastian Sanokowski Wilhelm Berghammer Sepp Hochreiter Sebastian Lehner 56 13 0 23 Nov 2023
Predict-Then-Optimize by Proxy: Learning Joint Models of Prediction and Optimization James Kotary Vincenzo Di Vito Jacob K Christopher Pascal Van Hentenryck Ferdinando Fioretto 36 3 0 22 Nov 2023
Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks Nasimeh Heydaribeni Xinrui Zhan Ruisi Zhang Tina Eliassi-Rad F. Koushanfar AI4CE 32 8 0 15 Nov 2023
Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach G. Marchetti Gabriele Cesa Kumar Pratik Arash Behboodi 34 2 0 14 Nov 2023
An Expandable Machine Learning-Optimization Framework to Sequential Decision-Making Dogacan Yilmaz ˙I. Esra B¨uy¨uktahtakın 16 12 0 12 Nov 2023
Differentiable Cutting-plane Layers for Mixed-integer Linear Optimization Gabriele Dragotto Stefan Clarke J. F. Fisac Bartolomeo Stellato 47 5 0 06 Nov 2023
Unveiling the Limits of Learned Local Search Heuristics: Are You the Mightiest of the Meek? Ankur Nath Alan Kuhnle 21 0 0 30 Oct 2023
Large Language Models as Evolutionary Optimizers Shengcai Liu Caishun Chen Xinghua Qu Jiaheng Zhang Yew-Soon Ong 27 92 0 29 Oct 2023
Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization Jinbiao Chen Jiahai Wang Zizhen Zhang Zhiguang Cao Te Ye Siyuan Chen 17 14 0 22 Oct 2023
Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement Jinbiao Chen Zizhen Zhang Zhiguang Cao Yaoxin Wu Yining Ma Te Ye Jiahai Wang 20 9 0 22 Oct 2023