Edge-Driven Multiple Trajectory Attention Model for Vehicle Routing Problems
The vehicle routing problem (VRP), as one of the classic combinatorial optimization problems, has garnered widespread attention in recent years. Existing deep reinforcement learning (DRL)-based methods predominantly focus on node information, neglecting the edge information inherent in the graph str...
Saved in:
| Main Authors: | Dapeng Yan, Bei Ou, Qingshu Guan, Zheng Zhu, Hui Cao |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/5/2679 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Graph-Driven Deep Reinforcement Learning for Vehicle Routing Problems with Pickup and Delivery
by: Dapeng Yan, et al.
Published: (2025-04-01) -
A Deep Reinforcement Learning-Based Decision-Making Approach for Routing Problems
by: Dapeng Yan, et al.
Published: (2025-04-01) -
Reinforcement Learning for Efficient Drone-Assisted Vehicle Routing
by: Aigerim Bogyrbayeva, et al.
Published: (2025-02-01) -
A Biased–Randomized Iterated Local Search with Round-Robin for the Periodic Vehicle Routing Problem
by: Juan F. Gomez, et al.
Published: (2025-08-01) -
Edge intelligence-assisted routing protocol for Internet of vehicles via reinforcement learning
by: Bingyi LIU, et al.
Published: (2023-11-01)