量子辅助的太空物流任务规划
Quantum-Assisted Space Logistics Mission Planning
AI总结：
本文针对太空物流中经典方法难以处理的大规模网络路径优化问题，采用熵量子计算将其建模为时变多商品网络流并求解，展示了量子计算在星际任务规划中的应用潜力。
摘要：
量子计算为解决大规模优化中传统上难以处理的问题提供了一种新方法。太空物流任务需要在复杂网络中高效规划有效载荷、航天器和资源的路径，这通常会导致解空间呈指数级增长，而经典方法无法高效求解。本文利用熵量子计算，将太空物流问题建模并求解为时变多商品网络流，从而能够探索大型解空间。研究结果突显了量子计算解决复杂航空航天物流问题的潜力，并证明了其适用于复杂的星际任务规划。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
