Xialiang Tong

According to our database1, Xialiang Tong authored at least 15 papers between 2019 and 2024.

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Bibliography

2024
Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization.
CoRR, 2024

An Example of Evolutionary Computation + Large Language Model Beating Human: Design of Efficient Guided Local Search.
CoRR, 2024

2023
Hybrid variable neighborhood search for automated warehouse scheduling.
Optim. Lett., December, 2023

Algorithm Evolution Using Large Language Model.
CoRR, 2023

Large Language Model for Multi-objective Evolutionary Optimization.
CoRR, 2023

Heuristics for Vehicle Routing Problem: A Survey and Recent Advances.
CoRR, 2023

2022
A Data-Driven Column Generation Algorithm For Bin Packing Problem in Manufacturing Industry.
CoRR, 2022

Introduction to The Dynamic Pickup and Delivery Problem Benchmark - ICAPS 2021 Competition.
CoRR, 2022

Exact algorithms for the multiple depot vehicle scheduling problem with heterogeneous vehicles, split loads and toll-by-weight scheme.
Comput. Ind. Eng., 2022

Bilevel learning for large-scale flexible flow shop scheduling.
Comput. Ind. Eng., 2022

2021
A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems.
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.
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.
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.
CoRR, 2020

2019
A Data-Driven Approach for Multi-level Packing Problems in Manufacturing Industry.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019


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