Graph attention, learning 2-opt algorithm for the traveling salesman problem
Abstract In recent years, deep graph neural networks (GNNs) have been used as solvers or helper functions for the traveling salesman problem (TSP), but they are usually used as encoders to generate static node representations for downstream tasks and are incapable of obtaining the dynamic permutatio...
Saved in:
Main Authors: | Jia Luo, Herui Heng, Geng Wu |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer
2025-01-01
|
Series: | Complex & Intelligent Systems |
Subjects: | |
Online Access: | https://doi.org/10.1007/s40747-024-01716-5 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Review of Swarm Intelligence for Solving Symmetric Traveling Salesman Problem
by: Awaz Ahmad Shaban, et al.
Published: (2023-07-01) -
Synchronization-based graph spatio-temporal attention network for seizure prediction
by: Jie Xiang, et al.
Published: (2025-02-01) -
Recommendation model combining review’s feature and rating graph convolutional representation
by: Hailin FENG, et al.
Published: (2022-03-01) -
When does metacognition evolve in the opt-out paradigm?
by: Robin Watson
Published: (2024-10-01) -
An Adaptive Spatio-Temporal Traffic Flow Prediction Using Self-Attention and Multi-Graph Networks
by: Basma Alsehaimi, et al.
Published: (2025-01-01)