A Lightweight CNN-Transformer Model for Learning Traveling Salesman Problems

arXiv:2305.01883v2 Announce Type: replace
Abstract: Several studies have attempted to solve traveling salesman problems (TSPs) using various deep learning techniques. Among them, Transformer-based models show state-of-the-art performance even for large-scale Traveling Salesman Problems (TSPs). However, they are based on fully-connected attention models and suffer from large computational complexity and GPU memory usage. Our work is the first CNN-Transformer model based on a CNN embedding layer and partial self-attention for TSP. Our CNN-Transformer model is able to better learn spatial features …

arxiv cnn cs.cg cs.lg transformer transformer model type