Calculating the Topological Resilience of Supply Chain Networks Using Quantum Hopfield Neural Networks

Abstract

A quantum computing approach is presented for implementing a quantum version of a Hopfield Neural Network which is then used for solving the Minimum Vertex Cover (MVC) problem. A bijection maps the Minimum Vertex Cover of a graph to a stable pattern of the Quantum Hopfield Neural Network. The proposed algorithm reached a 100% accuracy in finding the minimum vertex cover for a testing dataset of graphs. The use of the Quantum HNN and quantum principles such as superposition enables the usage of potentially exponential power and speed up in solving NP-complete graph problems such as the MVC.