  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.
