Quantum-Assisted Space Logistics Mission Planning

Abstract

Quantum computing provides a novel approach to addressing conventionally intractable issues in large-scale optimization. Space logistics missions require the efficient routing of payloads, spacecraft, and resources across complex networks, often resulting in an exponential growth of the solution space that classical methods cannot efficiently solve. This paper leverages entropy quantum computing to model and solve the space logistics problem as a time-dependent multicommodity network flow, enabling the exploration of large solution spaces. The findings highlight quantum computing's potential to address complex aerospace logistics, demonstrating its suitability for complex interplanetary mission planning.

References in corpus (4)

• The Variational Quantum Eigensolver: a review of methods and best practices
• A Tutorial on Formulating and Using QUBO Models
• Multi-Fidelity Space Mission Planning and Infrastructure Design Framework for Space Resource Logistics
• Hierarchical Reinforcement Learning Framework for Stochastic Spaceflight Campaign Design