Quantum Optimization for Solving NP-Hard Problems

Abstract

The University of Maryland has a lot of resources that it seeks to ensure every student has easy access to, ranging from facilities like Wi-fi to basic safety measures such as streetlights. Ensuring these resources are properly distributed amongst campus can grow to be expensive considering the University’s 1,339-acre estate. This optimization algorithm aims to minimize the resources necessary to ensure the entirety of any given area is fully encompassed by whatever facility the user desires. Quantum optimization is the ideal way to accomplish this task as classical optimizers are unable to provide as efficient of a solution due to the risk of getting trapped in local minima and the significantly weaker processing ability. The poorer performance of the classical optimizer is demonstrated in our results.