Unsupervised Learning for Solving the Travelling Salesman Problem

arXiv:2303.10538v2 Announce Type: replace-cross
Abstract: We propose UTSP, an unsupervised learning (UL) framework for solving the Travelling Salesman Problem (TSP). We train a Graph Neural Network (GNN) using a surrogate loss. The GNN outputs a heat map representing the probability for each edge to be part of the optimal path. We then apply local search to generate our final prediction based on the heat map. Our loss function consists of two parts: one pushes the model to find the shortest …

abstract arxiv cs.ai cs.lg edge framework gnn graph graph neural network heat loss map network neural network part path probability train type unsupervised unsupervised learning