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This paper develops a flexibility management framework for space logisticsmission planning under uncertainty through decision rules and multi-stagestochastic programming. It aims to add built-in flexibility to spacearchitectures in the phase of early-stage mission planning. The proposedframework integrates the decision rule formulation into a network-based spacelogistics optimization formulation model. It can output a series of decisionrules 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 environmentand mission demands. The generated decision rules and the Pareto front plot canhelp decision-makers create implementable policies immediately when uncertaintyevents occur during space missions. An example mission case study about spacestation resupply under rocket launch delay uncertainty is established todemonstrate the value of the proposed framework.

Flexibility Management for Space Logistics via Decision Rules