Conference PaperIntegrated Space Mission Planning Under Uncertainty via Stochastic and Decomposition-Based OptimizationIsaji, Masafumi; Ho, KokiAs we strive to establish a long-term presence in space, it is crucial to plan large-scale space missions and campaigns with future uncertainties in mind. However, integrated space mission planning, which simultaneously considers mission planning and spacecraft design, faces significant challenges when dealing with uncertainties; this problem is formulated as a stochastic mixed integer nonlinear program (MINLP), and solving it using the conventional method would be computationally prohibitive for realistic applications. Extending a deterministic decomposition method from our previous work, we propose a novel and computationally efficient approach for integrated space mission planning under uncertainty. The proposed method effectively combines the Alternating Direction Method of Multipliers (ADMM)-based decomposition framework from our previous work, robust optimization, and two-stage stochastic programming (TSSP).This hybrid approach first solves the integrated problem deterministically, assuming the worst scenario, to precompute the robust spacecraft design. Subsequently, the two-stage stochastic program is solved for mission planning, effectively transforming the problem into a more manageable mixed-integer linear program (MILP). This approach significantly reduces computational costs compared to the exact method, but may potentially miss solutions that the exact method might find. We examine this balance through a case study of staged infrastructure deployment on the lunar surface under future demand uncertainty. When comparing the proposed method with a fully coupled benchmark, the results indicate that our approach can achieve nearly identical objective values (no worse than 1% in solved problems) while drastically reducing computational costs.AIAA AVIATION FORUM AND ASCEND 20242024-07-2710541409https://doi.org/10.2514/6.2024-48161942559Las Vegas, NevadaNational Science Foundation