基于决策规则的空间物流灵活性管理
Flexibility Management for Space Logistics via Decision Rules
AI总结：
本文针对不确定条件下的空间物流任务规划，提出基于决策规则和多阶段随机规划的灵活性管理框架，集成决策规则与网络优化模型生成帕累托前沿和决策规则，通过空间站补给案例验证其价值。
摘要：
本文通过决策规则和多阶段随机规划，为不确定条件下的空间物流任务规划开发了一个灵活性管理框架，旨在为早期任务规划阶段的空间架构增加内置灵活性。该框架将决策规则公式集成到基于网络的空间物流优化模型中，可输出一系列决策规则，并在考虑环境和任务需求不确定性的情况下，生成预期任务成本（即近地轨道初始质量）与预期任务性能（即有效乘员工作时间）之间的帕累托前沿。生成的决策规则和帕累托前沿图能帮助决策者在空间任务中出现不确定事件时立即制定可执行策略。本文建立了一个考虑火箭发射延迟不确定性的空间站补给任务案例研究，以证明该框架的价值。
英文摘要：
This paper develops a flexibility management framework for space logistics mission planning under uncertainty through decision rules and multi-stage stochastic programming. It aims to add built-in flexibility to space architectures in the phase of early-stage mission planning. The proposed framework integrates the decision rule formulation into a network-based space logistics optimization formulation model. It can output a series of decision rules and generate a Pareto front between the expected mission cost (i.e., initial mass in low-Earth orbit) and the expected mission performance (i.e., effective crew operating time) considering the uncertainty in the environment and mission demands. The generated decision rules and the Pareto front plot can help decision-makers create implementable policies immediately when uncertainty events occur during space missions. An example mission case study about space station resupply under rocket launch delay uncertainty is established to demonstrate the value of the proposed framework.
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。
