4 papers
Human-Human & Human-Robot Interaction Transformer (H2INT) for Robot Navigation in Dense and Uncertain Crowds
Ao Shen, Kaixi Chen, Shiwei Liu +2
Safe robot navigation in dense crowds requires reasoning about pedestrian motion and how it may change in response to a robot. However, many learning-based approaches generate pede…
Towards Generalization-Oriented Models for Vehicle Routing Problems with Mixture-of-Experts
Changhao Miao, Yuntian Zhang, Tongyu Wu +2
In recent years, Deep Reinforcement Learning (DRL) has achieved substantial progress on Vehicle Routing Problems (VRPs). However, existing DRL-based methods are typically trained o…
Adversarial Training for Robust Coverage Network under Worst-case Facility Losses
Changhao Miao, Yuntian Zhang, Tongyu Wu +2
The Maximal Covering Location-Interdiction Problem (MCLIP) is a classic bi-level optimization problem, which is fundamental to resilient infrastructure planning yet remains computa…
An End-to-End Learning Approach for Solving Capacitated Location-Routing Problems
Changhao Miao, Yuntian Zhang, Tongyu Wu +2
The capacitated location-routing problems (CLRPs) are classical problems in combinatorial optimization, which require simultaneously making location and routing decisions. In CLRPs…