Flexibility Management for Space Logistics via Decision Rules

TL;DR

This paper introduces a decision rule-based framework for space logistics planning that manages uncertainty effectively, providing actionable policies and trade-offs between cost and performance for space missions.

Contribution

It develops a novel multi-stage stochastic programming approach with decision rules integrated into space logistics optimization, enabling real-time policy generation under uncertainty.

Findings

Decision rules effectively handle launch delay uncertainties.

Framework produces Pareto front for cost-performance trade-offs.

Case study demonstrates practical applicability in space station resupply.

Abstract

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.