Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Add one paper from IJCAI'24 #29

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
46 changes: 25 additions & 21 deletions README.md
Original file line number Diff line number Diff line change
@@ -445,75 +445,71 @@ We mark work contributed by [Thinklab](http://thinklab.sjtu.edu.cn) with ⭐.

*Zhou Jianan, Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang*

40. **Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=RBI4oAbdpm), [code](https://github.com/CIAM-Group/NCO_code/tree/main/single_objective/LEHD)

*Luo, Fu and Lin, Xi and Liu, Fei and Zhang, Qingfu and Wang, Zhenkun*

41. **DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=JV8Ff0lgVV), [code](https://github.com/Edward-Sun/DIFUSCO)
40. **DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=JV8Ff0lgVV), [code](https://github.com/Edward-Sun/DIFUSCO)

*Zhiqing Sun, Yiming Yang*

42. **DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=cd5D1DD923), [code](https://github.com/henry-yeh/DeepACO)
41. **DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=cd5D1DD923), [code](https://github.com/henry-yeh/DeepACO)

*Ye, Haoran and Wang, Jiarui and Cao, Zhiguang and Liang, Helan and Li, Yong*

43. **Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=v6VpqGcGAR)
42. **Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=v6VpqGcGAR)

*Grinsztajn, Nathan and Furelos-Blanco, Daniel and Surana, Shikha and Bonnet, Cl{\'e}ment and Barrett, Thomas D*

44. **Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods** NeurIPS, 2023. [paper](https://openreview.net/forum?id=mmTy1iyU5G), [code](https://openreview.net/attachment?id=mmTy1iyU5G&name=supplementary_material)
43. **Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods** NeurIPS, 2023. [paper](https://openreview.net/forum?id=mmTy1iyU5G), [code](https://openreview.net/attachment?id=mmTy1iyU5G&name=supplementary_material)

*Caramanis, Constantine and Fotakis, Dimitris and Kalavasis, Alkis and Kontonis, Vasilis and Tzamos, Christos*

45. **Combinatorial Optimization with Policy Adaptation using Latent Space Search** NeurIPS, 2023. [paper](https://openreview.net/forum?id=vpMBqdt9Hl)
44. **Combinatorial Optimization with Policy Adaptation using Latent Space Search** NeurIPS, 2023. [paper](https://openreview.net/forum?id=vpMBqdt9Hl)

*Chalumeau, Felix and Surana, Shikha and Bonnet, Cl{\'e}ment and Grinsztajn, Nathan and Pretorius, Arnu and Laterre, Alexandre and Barrett, Thomas D*

46. **Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=593fc38lhN), [code](https://github.com/bill-cjb/EMNH)
45. **Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=593fc38lhN), [code](https://github.com/bill-cjb/EMNH)

*Chen, Jinbiao and Wang, Jiahai and Zhang, Zizhen and Cao, Zhiguang and Ye, Te and Chen, Siyuan*

47. **BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial Optimization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=BRqlkTDvvm), [code](https://github.com/naver/bq-nco)
46. **BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial Optimization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=BRqlkTDvvm), [code](https://github.com/naver/bq-nco)

*Drakulic, Darko and Michel, Sofia and Mai, Florian and Sors, Arnaud and Andreoli, Jean-Marc*

48. **Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=RBI4oAbdpm), [code](https://github.com/CIAM-Group/NCO_code/tree/main/single_objective/LEHD)
47. **Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=RBI4oAbdpm), [code](https://github.com/CIAM-Group/NCO_code/tree/main/single_objective/LEHD)

*Luo, Fu and Lin, Xi and Liu, Fei and Zhang, Qingfu and Wang, Zhenkun*

49. **Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement** NeurIPS, 2023. [paper](https://openreview.net/forum?id=N4JkStI1fe), [code](https://github.com/bill-cjb/NHDE)
48. **Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement** NeurIPS, 2023. [paper](https://openreview.net/forum?id=N4JkStI1fe), [code](https://github.com/bill-cjb/NHDE)

*Chen, Jinbiao and Zhang, Zizhen and Cao, Zhiguang and Wu, Yaoxin and Ma, Yining and Ye, Te and Wang, Jiahai*

50. **Unsupervised Learning for Solving the Travelling Salesman Problem** NeurIPS, 2023. [paper](https://openreview.net/forum?id=lAEc7aIW20)
49. **Unsupervised Learning for Solving the Travelling Salesman Problem** NeurIPS, 2023. [paper](https://openreview.net/forum?id=lAEc7aIW20)

*Min, Yimeng and Bai, Yiwei and Gomes, Carla P*

51. **Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift** NeurIPS, 2023. [paper](https://openreview.net/forum?id=HoBbZ1vPAh)
50. **Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift** NeurIPS, 2023. [paper](https://openreview.net/forum?id=HoBbZ1vPAh)

*Jiang, Yuan and Cao, Zhiguang and Wu, Yaoxin and Song, Wen and Zhang, Jie*

52. **Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt** NeurIPS, 2023. [paper](https://openreview.net/forum?id=q1JukwH2yP), [code](https://github.com/yining043/NeuOpt)
51. **Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt** NeurIPS, 2023. [paper](https://openreview.net/forum?id=q1JukwH2yP), [code](https://github.com/yining043/NeuOpt)

*Ma, Yining and Cao, Zhiguang and Chee, Yeow Meng*

53. **⭐From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=JtF0ugNMv2), [code](https://github.com/Thinklab-SJTU/T2TCO)
52. **⭐From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization** NeurIPS, 2023. [paper](https://openreview.net/forum?id=JtF0ugNMv2), [code](https://github.com/Thinklab-SJTU/T2TCO)

*Yang Li, Jinpei Guo, Runzhong Wang, Junchi Yan*

54. **Reinforced Lin–Kernighan–Helsgaun Algorithms for the Traveling Salesman Problems** Knowledge-Based Systems, 2023. [journal](https://www.sciencedirect.com/science/article/pii/S0950705122012400), [code](https://github.com/JHL-HUST/VSR-LKH-V2)
53. **Reinforced Lin–Kernighan–Helsgaun Algorithms for the Traveling Salesman Problems** Knowledge-Based Systems, 2023. [journal](https://www.sciencedirect.com/science/article/pii/S0950705122012400), [code](https://github.com/JHL-HUST/VSR-LKH-V2)

*Jiongzhi Zheng, Kun He, Jianrong Zhou, Yan Jin, Chu-Min Li*

55. **GLOP: Learning Global Partition and Local Construction for Solving Large-Scale Routing Problems in Real-Time** AAAI, 2024. [paper](https://arxiv.org/abs/2312.08224), [code](https://github.com/henry-yeh/GLOP)
54. **GLOP: Learning Global Partition and Local Construction for Solving Large-Scale Routing Problems in Real-Time** AAAI, 2024. [paper](https://arxiv.org/abs/2312.08224), [code](https://github.com/henry-yeh/GLOP)

*Haoran Ye, Jiarui Wang, Helan Liang, Zhiguang Cao, Yong Li, Fanzhang Li*

56. **Distilling Autoregressive Models to Obtain High-Performance Non-autoregressive Solvers for Vehicle Routing Problems with Faster Inference Speed** AAAI, 2024. [paper](https://arxiv.org/abs/2312.12469), [code](https://github.com/xybFight/GNARKD)
55. **Distilling Autoregressive Models to Obtain High-Performance Non-autoregressive Solvers for Vehicle Routing Problems with Faster Inference Speed** AAAI, 2024. [paper](https://arxiv.org/abs/2312.12469), [code](https://github.com/xybFight/GNARKD)

*Yubin Xiao, Di Wang, Boyang Li, Mingzhao Wang, Xuan Wu, Changliang Zhou, You Zhou*

57. **Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems** ICML, 2024. [paper](https://arxiv.org/abs/2406.03503), [code](https://github.com/xyfffff/rethink_mcts_for_tsp)
56. **Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems** ICML, 2024. [paper](https://arxiv.org/abs/2406.03503), [code](https://github.com/xyfffff/rethink_mcts_for_tsp)

*Yifan Xia, Xianliang Yang, Zichuan Liu, Zhihao Liu, Lei Song, Jiang Bian*

@@ -723,6 +719,10 @@ We mark work contributed by [Thinklab](http://thinklab.sjtu.edu.cn) with ⭐.

*James Fitzpatrick, Deepak Ajwani, Paula Carroll*

36. **A Neural Column Generation Approach to the Vehicle Routing Problem with Two-Dimensional Loading and Last-In-First-Out Constraints** IJCAI, 2024. [paper](https://www.ijcai.org/proceedings/2024/0218.pdf), [code](https://github.com/xyfffff/NCG-for-2L-CVRP)

*Yifan Xia, Xiangyi Zhang*

### [Job Shop Scheduling Problem](#content)

1. **Smart Manufacturing Scheduling With Edge Computing Using Multiclass Deep Q Network** Transactions on Industrial Informatics, 2019. [journal](https://ieeexplore.ieee.org/document/8676376)
@@ -1044,6 +1044,10 @@ Knapsack,A Pointer Network Based Deep Learning Algorithm for 0-1 Knapsack Probl

*Pan, Yuxin and Chen, Yize and Lin, Fangzhen*

25. **A Neural Column Generation Approach to the Vehicle Routing Problem with Two-Dimensional Loading and Last-In-First-Out Constraints** IJCAI, 2024. [paper](https://www.ijcai.org/proceedings/2024/0218.pdf), [code](https://github.com/xyfffff/NCG-for-2L-CVRP)

*Yifan Xia, Xiangyi Zhang*

### [Graph Edit Distance](#content)

1. **SimGNN - A Neural Network Approach to Fast Graph Similarity Computation** WSDM, 2019. [paper](https://arxiv.org/abs/1808.05689), [code](https://github.com/yunshengb/SimGNN)
1 change: 1 addition & 0 deletions data/papers.csv
Original file line number Diff line number Diff line change
@@ -110,6 +110,7 @@ Vehicle Routing Problem,Learning to Delegate for Large-scale Vehicle Routing,Neu
Vehicle Routing Problem,Learning a Latent Search Space for Routing Problems using Variational Autoencoders,ICLR,2021,paper,https://openreview.net/forum?id=90JprVrJBO,"Hottung, Andre and Bhandari, Bhanu and Tierney, Kevin",
Vehicle Routing Problem,A Scalable Learning Approach for the Capacitated Vehicle Routing Problem,Computers and Operations Research,2024,journal,https://dx.doi.org/10.1016/j.cor.2024.106787,"James Fitzpatrick, Deepak Ajwani, Paula Carroll",
Vehicle Routing Problem,Learning to Prune Electric Vehicle Routing Problems,LION,2023,paper,https://link.springer.com/chapter/10.1007/978-3-031-44505-7_26,"James Fitzpatrick, Deepak Ajwani, Paula Carroll",
Vehicle Routing Problem; Bin Packing Problem,A Neural Column Generation Approach to the Vehicle Routing Problem with Two-Dimensional Loading and Last-In-First-Out Constraints,IJCAI,2024,paper,https://www.ijcai.org/proceedings/2024/0218.pdf,"Yifan Xia, Xiangyi Zhang",https://github.com/xyfffff/NCG-for-2L-CVRP
Computing Resource Allocation,Resource Management with Deep Reinforcement Learning.,HotNets,2016,paper,https://dl.acm.org/doi/abs/10.1145/3005745.3005750,"Mao, Hongzi and Alizadeh, Mohammad and Menache, Ishai and Kandula, Srikanth.",
Computing Resource Allocation,Learning Scheduling Algorithms for Data Processing Clusters,SIGCOMM,2019,paper,https://static.aminer.cn/storage/pdf/arxiv/18/1810/1810.01963.pdf,"Mao, Hongzi and Schwarzkopf, Malte and Venkatakrishnan, Bojja Shaileshh and Meng, Zili and Alizadeh, Mohammad.",https://github.com/hongzimao/decima-sim
Computing Resource Allocation,Smart Resource Allocation for Mobile Edge Computing: A Deep Reinforcement Learning Approach,IEEE Transactions on Emerging Topics in Computing,2019,Paper,https://ieeexplore.ieee.org/abstract/document/8657791,Jiadai; Lei Zhao; Jiajia Liu; Nei Kato,