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
Towards Invertible Semantic-Preserving Embeddings of Logical Formulae Gaia Saveri Luca Bortolussi NAI 46 3 0 03 May 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 94 32 0 29 Apr 2023
H-TSP: Hierarchically Solving the Large-Scale Travelling Salesman Problem Xuanhao Pan Yan Jin Yuandong Ding Ming Feng Li Zhao Lei Song Jiang Bian 11 35 0 19 Apr 2023
A Scalable Test Problem Generator for Sequential Transfer Optimization Xiaoming Xue Cuie Yang Liang Feng Kai Zhang Linqi Song Kay Chen Tan 17 11 0 17 Apr 2023
Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research Perspective Nijat Mehdiyev Maxim Majlatow Peter Fettke 32 11 0 13 Apr 2023
Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks George Watkins Giovanni Montana Juergen Branke GNN 24 4 0 08 Apr 2023
Combinatorial Optimization enriched Machine Learning to solve the Dynamic Vehicle Routing Problem with Time Windows Léo Baty Kai Jungel P. Klein Axel Parmentier Maximilian Schiffer 11 28 0 03 Apr 2023
Graph Neural Networks for the Offline Nanosatellite Task Scheduling Problem Bruno Machado Pacheco L. O. Seman C. A. Rigo E. Camponogara E. Bezerra L. Coelho 41 1 0 24 Mar 2023
Unsupervised Learning for Solving the Travelling Salesman Problem Yimeng Min Yiwei Bai Carla P. Gomes OT 23 36 0 19 Mar 2023
A hybrid deep-learning-metaheuristic framework for bi-level network design problems B. Madadi Gonçalo Homem de Almeida Rodriguez Correia 16 4 0 10 Mar 2023
Preference-Aware Delivery Planning for Last-Mile Logistics Qian Shao Shih-Fen Cheng 14 1 0 08 Mar 2023
Neural Airport Ground Handling Yaoxin Wu Jianan Zhou Yunwen Xia Xianli Zhang Zhiguang Cao Jie Zhang AI4TS 48 10 0 04 Mar 2023
Heuristics for Vehicle Routing Problem: A Survey and Recent Advances Fei Liu Chengyu Lu Lin Gui Qingfu Zhang Xialiang Tong M. Yuan 25 15 0 01 Mar 2023
ASP: Learn a Universal Neural Solver! Chenguang Wang Zhouliang Yu Stephen Marcus McAleer Tianshu Yu Yao-Chun Yang AAML 32 24 0 01 Mar 2023
Graph Reinforcement Learning for Operator Selection in the ALNS Metaheuristic Syu-Ning Johnn Victor-Alexandru Darvariu J. Handl Joerg Kalcsics 13 2 0 28 Feb 2023
WISK: A Workload-aware Learned Index for Spatial Keyword Queries Yufan Sheng Xin Cao Yixiang Fang Kaiqi Zhao Jianzhong Qi Gao Cong Wenjie Zhang 12 17 0 28 Feb 2023
Machine Learning for Cutting Planes in Integer Programming: A Survey Arnaud Deza Elias Boutros Khalil 25 24 0 17 Feb 2023
Semiconductor Fab Scheduling with Self-Supervised and Reinforcement Learning Pierre Tassel Benjamin Kovács M. Gebser Konstantin Schekotihin Patrick Stöckermann Georg Seidel 15 5 0 14 Feb 2023
Learning-based Online Optimization for Autonomous Mobility-on-Demand Fleet Control Kai Jungel Axel Parmentier Maximilian Schiffer Thibaut Vidal 18 11 0 08 Feb 2023
Digital Twin Applications in Urban Logistics: An Overview Abdo Abouelrous Laurens Bliek Yingqian Zhang AI4CE 13 15 0 01 Feb 2023
Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model Zhihai Wang Xijun Li Jie Wang Yufei Kuang M. Yuan Jianguo Zeng Yongdong Zhang Feng Wu 26 39 0 01 Feb 2023
Partitioning Distributed Compute Jobs with Reinforcement Learning and Graph Neural Networks Christopher W. F. Parsonson Zacharaya Shabka Alessandro Ottino G. Zervas 34 0 0 31 Jan 2023
Learning Coordination Policies over Heterogeneous Graphs for Human-Robot Teams via Recurrent Neural Schedule Propagation Batuhan Altundas Zheyuan Wang Joshua Bishop Matthew C. Gombolay 31 4 0 30 Jan 2023
A Sequential Deep Learning Algorithm for Sampled Mixed-integer Optimisation Problems M. Chamanbaz Roland Bouffanais 6 1 0 25 Jan 2023
Learning To Dive In Branch And Bound Max B. Paulus Andreas Krause 29 4 0 24 Jan 2023
Two-Stage Learning For the Flexible Job Shop Scheduling Problem Wenbo Chen Reem Khir Pascal Van Hentenryck 17 4 0 23 Jan 2023
Robust Scheduling with GFlowNets David W. Zhang Corrado Rainone M. Peschl Roberto Bondesan 29 49 0 17 Jan 2023
BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial Optimization Darko Drakulic Sofia Michel Florian Mai Arnaud Sors J. Andreoli OffRL 41 32 0 09 Jan 2023
Learning a Generic Value-Selection Heuristic Inside a Constraint Programming Solver Tom Marty Tristan François Pierre Tessier Louis Gautier Louis-Martin Rousseau Quentin Cappart 46 7 0 05 Jan 2023
A machine learning framework for neighbor generation in metaheuristic search De-You Liu Vincent Perreault A. Hertz Andrea Lodi 14 7 0 22 Dec 2022
Learning to repeatedly solve routing problems Mouad Morabit G. Desaulniers Andrea Lodi 17 3 0 15 Dec 2022
Learning Markov Random Fields for Combinatorial Structures via Sampling through Lovász Local Lemma Nan Jiang Yi Gu Yexiang Xue 27 0 0 01 Dec 2022
Denoising Diffusion for Sampling SAT Solutions Kārlis Freivalds Sergejs Kozlovics 13 2 0 30 Nov 2022
Enhancing Constraint Programming via Supervised Learning for Job Shop Scheduling Yuan Sun Su Nguyen D. Thiruvady Xiaodong Li Andreas T. Ernst U. Aickelin 12 2 0 26 Nov 2022
How to predict and optimise with asymmetric error metrics M. Abolghasemi Richard Bean 14 4 0 24 Nov 2022
Actively Learning Costly Reward Functions for Reinforcement Learning André Eberhard Houssam Metni G. Fahland A. Stroh Pascal Friederich OffRL 35 0 0 23 Nov 2022
UNSAT Solver Synthesis via Monte Carlo Forest Search Chris Cameron Jason S. Hartford Taylor Lundy T. Truong Alan Milligan Rex Chen Kevin Leyton-Brown 21 1 0 22 Nov 2022
Arbitrarily Large Labelled Random Satisfiability Formulas for Machine Learning Training D. Achlioptas Amrit Daswaney Periklis A. Papakonstantinou NAI BDL 15 0 0 21 Nov 2022
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling Cong Zhang Zhiguang Cao Wen Song Puay Siew Tan Jie Zhang 17 15 0 20 Nov 2022
A Survey on Influence Maximization: From an ML-Based Combinatorial Optimization Yandi Li Haobo Gao Yunxuan Gao Jianxiong Guo Weili Wu 24 38 0 06 Nov 2022
Learning to Optimize Permutation Flow Shop Scheduling via Graph-based Imitation Learning Longkang Li Siyuan Liang Zihao Zhu Chris H. Q. Ding Hong Zha Baoyuan Wu AI4CE 7 7 0 31 Oct 2022
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
End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location Shiqing Liu Xueming Yan Yaochu Jin 37 9 0 27 Oct 2022
SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems Aaron Ferber Taoan Huang Daochen Zha M. Schubert Benoit Steiner B. Dilkina Yuandong Tian 41 20 0 22 Oct 2022
Machine Learning for K-adaptability in Two-stage Robust Optimization Esther Julien Krzysztof Postek cS. .Ilker Birbil 36 2 0 20 Oct 2022
On Representing Mixed-Integer Linear Programs by Graph Neural Networks Ziang Chen Jialin Liu Xinshang Wang Jian Lu W. Yin AI4CE 32 16 0 19 Oct 2022
ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning Tiantian Chen Siwen Yan Jianxiong Guo Weili Wu 14 22 0 14 Oct 2022
Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization Nathan Grinsztajn Daniel Furelos-Blanco Shikha Surana Clément Bonnet Thomas D. Barrett 54 28 0 07 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
Deep Attentive Belief Propagation: Integrating Reasoning and Learning for Solving Constraint Optimization Problems Yanchen Deng Shufeng Kong Caihua Liu Bo An 11 4 0 24 Sep 2022