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Add one paper from IJCAI'24 #29

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46 changes: 25 additions & 21 deletions README.md
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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
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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,