Flexibility Management for Space Logistics via Decision Rules

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 architectures in the phase of early-stage planning. The proposed integrates rule formulation into network-based optimization model. can output series generate Pareto front between expected cost (i.e., initial mass low Earth orbit) performance effective crew operating time), considering environment demands. generated plot help makers create implementable policies immediately when events occur during missions. An example case study about station resupply rocket launch delay is established demonstrate value framework.