1、Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems
Code: https://github.com/CIAM-Group/SIL
简介: 针对大规模车辆路径问题（VRP）的神经组合优化方法
2、Rethinking Light Decoder-based Solvers for Vehicle Routing Problems
Code: https://github.com/ziweileonhuang/reld-nco
**简介:**重新思考用于车辆路径问题的轻量级解码器
3、GOAL: A Generalist Combinatorial Optimization Agent Learner
Code: https://github.com/naver/goal-co
简介: 一个通用的组合优化智能体学习框架
4、Learning to Explore and Exploit with GNNs for Unsupervised Combinatorial Optimization
Code: https://github.com/utkuumur/X2GNN
简介: 利用图神经网络（GNN）在无监督组合优化中进行探索与利用
5、Adversarial Generative Flow Network for Solving Vehicle Routing Problems
Code: https://github.com/ZHANG-NI/AGFN
简介: 使用对抗生成流网络解决车辆路径问题
6、Efficient Discovery of Pareto Front for Multi-Objective Reinforcement Learning
**Code:**https://github.com/RuohLiuq/C-MORL
**简介：**高效发现多目标强化学习中的帕累托前沿，解决多目标优化权衡问题。