This paper develops a flexibility management framework for space logistics mission planning under uncertainty through decision rules and multistage 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.

本文通过决策规则和多阶段随机规划，为不确定性条件下的空间物流任务规划开发了一种柔性管理框架。它的目的是在早期任务计划阶段为太空架构增加内置的灵活性。所提出的框架将决策规则制定整合到基于网络的空间物流优化制定模型中。考虑到环境和任务的不确定性，它可以输出一系列决策规则，并在预期任务成本（即低地球轨道的初始质量）和预期任务性能（即有效的机组运行时间）之间生成帕累托前沿。需要。当太空任务期间发生不确定性事件时，生成的决策规则和Pareto前部图可以帮助决策者立即制定可实施的策略。建立了有关火箭发射延迟不确定性下空间站补给的任务实例研究，以证明所提出框架的价值。