Xialiang Tong

According to our database, Xialiang Tong authored at least 23 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A Systematic Survey on Large Language Models for Algorithm Design.

Fei Liu, Yiming Yao, Ping Guo, Zhiyuan Yang, Zhe Zhao, Xi Lin, Xialiang Tong, Mingxuan Yuan, Zhichao Lu, Zhenkun Wang, Qingfu Zhang

CoRR, 2024

UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems.

Zhi Zheng, Changliang Zhou, Xialiang Tong, Mingxuan Yuan, Zhenkun Wang

CoRR, 2024

Instance-Conditioned Adaptation for Large-scale Generalization of Neural Combinatorial Optimization.

Changliang Zhou, Xi Lin, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang

CoRR, 2024

Self-Improved Learning for Scalable Neural Combinatorial Optimization.

Fu Luo, Xi Lin, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang

CoRR, 2024

Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization.

Fei Liu, Xi Lin, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan

CoRR, 2024

An Example of Evolutionary Computation + Large Language Model Beating Human: Design of Efficient Guided Local Search.

Fei Liu, Xialiang Tong, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, Qingfu Zhang

CoRR, 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

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Prompt Learning for Generalized Vehicle Routing.

Fei Liu, Xi Lin, Weiduo Liao, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems.

Zhi Zheng, Shunyu Yao, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Ke Tang

Proceedings of the Forty-first International Conference on Machine Learning, 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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Hybrid variable neighborhood search for automated warehouse scheduling.

Ivan A. Davydov, Yury Kochetov, Daniil Tolstykh, Xialiang Tong, Jiawen Liu

Optim. Lett., December, 2023

Algorithm Evolution Using Large Language Model.

Fei Liu, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang

CoRR, 2023

Large Language Model for Multi-objective Evolutionary Optimization.

Fei Liu, Xi Lin, Zhenkun Wang, Shunyu Yao, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang

CoRR, 2023

Heuristics for Vehicle Routing Problem: A Survey and Recent Advances.

Fei Liu, Chengyu Lu, Lin Gui, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan

CoRR, 2023

2022

A Data-Driven Column Generation Algorithm For Bin Packing Problem in Manufacturing Industry.

Jiahui Duan, Xialiang Tong, Fei Ni, Zhenan He, Lei Chen, Mingxuan Yuan

CoRR, 2022

Introduction to The Dynamic Pickup and Delivery Problem Benchmark - ICAPS 2021 Competition.

Jianye Hao, Jiawen Lu, Xijun Li, Xialiang Tong, Xiang Xiang, Mingxuan Yuan, Hankz Hankui Zhuo

CoRR, 2022

Exact algorithms for the multiple depot vehicle scheduling problem with heterogeneous vehicles, split loads and toll-by-weight scheme.

Jiliu Li, Hu Qin, Huaxiao Shen, Xialiang Tong, Zhou Xu

Comput. Ind. Eng., 2022

Bilevel learning for large-scale flexible flow shop scheduling.

Longkang Li, Xiaojin Fu, Hui-Ling Zhen, Mingxuan Yuan, Jun Wang, Jiawen Lu, Xialiang Tong, Jia Zeng, Dirk Schnieders

Comput. Ind. Eng., 2022

2021

A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems.

Yi Ma, Xiaotian Hao, Jianye Hao, Jiawen Lu, Xing Liu, Xialiang Tong, Mingxuan Yuan, Zhigang Li, Jie Tang, Zhaopeng Meng

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Multi-Graph Attributed Reinforcement Learning based Optimization Algorithm for Large-scale Hybrid Flow Shop Scheduling Problem.

Fei Ni, Jianye Hao, Jiawen Lu, Xialiang Tong, Mingxuan Yuan, Jiahui Duan, Yi Ma, Kun He

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Learning to Pack: A Data-Driven Tree Search Algorithm for Large-Scale 3D Bin Packing Problem.

Qianwen Zhu, Xihan Li, Zihan Zhang, Zhixing Luo, Xialiang Tong, Mingxuan Yuan, Jia Zeng

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Bilevel Learning Model Towards Industrial Scheduling.

Longkang Li, Hui-Ling Zhen, Mingxuan Yuan, Jiawen Lu, Xialiang Tong, Jia Zeng, Jun Wang, Dirk Schnieders

CoRR, 2020

2019

A Data-Driven Approach for Multi-level Packing Problems in Manufacturing Industry.

Lei Chen, Xialiang Tong, Mingxuan Yuan, Jia Zeng, Lei Chen

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019