Name
Title | ||
|---|---|---|
Heterogeneous Attentions for Solving Pickup and Delivery Problem via Deep Reinforcement Learning |
Abstract | ||
|---|---|---|
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 visiting. However, existing methods could not handle well the pairing and precedence relationships in the pickup and delivery problem (PDP), which is a representative variant of VRP. To address this challenging issue, we ... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TITS.2021.3056120 | IEEE Transactions on Intelligent Transportation Systems |
Keywords | DocType | Volume |
Reinforcement learning,Routing,Peer-to-peer computing,Heuristic algorithms,Deep learning,Decoding,Decision making | Journal | 23 |
Issue | ISSN | Citations |
3 | 1524-9050 | 1 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jingwen Li | 1 | 33 | 12.58 |
| Liang Xin | 2 | 5 | 1.42 |
| zhiguang cao | 3 | 39 | 4.30 |
| Andrew Lim | 4 | 1 | 0.34 |
| Wen Song | 5 | 8 | 4.17 |
| Jie Zhang | 6 | 1995 | 156.26 |