275 citations · 1.2k across the 15 of their papers we have counts for
6 papers · 1 filter
Learning Large Neighborhood Search Policy for Integer Programming
Yaoxin Wu, Wen Song, Zhiguang Cao +1
We propose a deep reinforcement learning (RL) method to learn large neighborhood search (LNS) policy for integer programming (IP). The RL policy is trained as the destroy operator…
NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem
Liang Xin, Wen Song, Zhiguang Cao +1
We present NeuroLKH, a novel algorithm that combines deep learning with the strong traditional heuristic Lin-Kernighan-Helsgaun (LKH) for solving Traveling Salesman Problem. Specif…
Heterogeneous Attentions for Solving Pickup and Delivery Problem via Deep Reinforcement Learning
Jingwen Li, Liang Xin, Zhiguang Cao +3
Recently, there is an emerging trend to apply deep reinforcement learning to solve the vehicle routing problem (VRP), where a learnt policy governs the selection of next node for v…
Deep Reinforcement Learning for Solving the Heterogeneous Capacitated Vehicle Routing Problem
Jingwen Li, Yining Ma, Ruize Gao +4
Existing deep reinforcement learning (DRL) based methods for solving the capacitated vehicle routing problem (CVRP) intrinsically cope with homogeneous vehicle fleet, in which the…
Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer
Yining Ma, Jingwen Li, Zhiguang Cao +4
Recently, Transformer has become a prevailing deep architecture for solving vehicle routing problems (VRPs). However, it is less effective in learning improvement models for VRP be…
Dual Aspect Self-Attention based on Transformer for Remaining Useful Life Prediction
Zhizheng Zhang, Wen Song, Qiqiang Li
Remaining useful life prediction (RUL) is one of the key technologies of condition-based maintenance, which is important to maintain the reliability and safety of industrial equipm…