Awesome

EMNH

Code for NeurIPS2023 Paper: Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization

Quick Start

• To train a model, such as MOTSP with 20 nodes, set TSP_SIZE=20 and MODE=1 in HYPER_PARAMS.py, and then run run.py in the corresponding folder.
• To fine-tune and test a model, such as MOTSP with 20 nodes, set TSP_SIZE=20 and MODE=2 in HYPER_PARAMS.py, and then run run.py in the corresponding folder.
• Pretrained models for each problem can be found in the result folder.

Reference

If our work is helpful for your research, please cite our paper:

@inproceedings{chen2023efficient,
  title={Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization},
  author={Chen, Jinbiao and Wang, Jiahai and Zhang, Zizhen and Cao, Zhiguang and Ye, Te and Siyuan, Chen},
  booktitle={Advances in Neural Information Processing Systems},
  year={2023},
}