Revisit the Algorithm Selection Problem for TSP with Spatial Information Enhanced Graph Neural Networks

Ya Song, Laurens Bliek, Yingqian Zhang

2025

Abstract

Algorithm selection is a well-known problem where researchers investigate how to construct useful features representing the problem instances and then apply feature-based machine learning models to predict the best algorithm for each instance. However, even for simple optimization problems like Euclidean Traveling Salesman Problem (TSP), there lacks a general and effective feature representation for problem instances. The important features of TSP are relatively well understood in the literature, based on extensive domain knowledge and post-analysis of the solutions. In recent years, Convolutional Neural Network (CNN) has gained popularity for TSP algorithm selection. Compared to traditional feature-based models, CNN has an automatic feature-learning ability and demands less domain expertise. However, it is still required to generate intermediate representations, i.e., multiple images to represent TSP instances first. In this paper, we revisit algorithm selection for TSP and propose GINES, a new Graph Neural Network (GNN) that uses city coordinates and distances as input. GINES introduces a novel message-passing mechanism and local feature extractor to learn TSP’s spatial information. Evaluation of two benchmarks shows GINES outperforms CNN and GINE models and surpasses traditional feature-based methods on one dataset. Our codes and datasets are available at https://github.com/lurenyi233/GINES TSP.

Paper Citation

in Harvard Style

Song Y., Bliek L. and Zhang Y. (2025). Revisit the Algorithm Selection Problem for TSP with Spatial Information Enhanced Graph Neural Networks. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 472-479. DOI: 10.5220/0013153400003890

in Bibtex Style

@conference{icaart25,
author={Ya Song and Laurens Bliek and Yingqian Zhang},
title={Revisit the Algorithm Selection Problem for TSP with Spatial Information Enhanced Graph Neural Networks},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={472-479},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013153400003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Revisit the Algorithm Selection Problem for TSP with Spatial Information Enhanced Graph Neural Networks
SN - 978-989-758-737-5
AU - Song Y.
AU - Bliek L.
AU - Zhang Y.
PY - 2025
SP - 472
EP - 479
DO - 10.5220/0013153400003890
PB - SciTePress