A Stochastic Modeling Approach for Interplanetary Supply Chain Planning

Abstract

The unique and complex challenges of sustainable interplanetary travel necessitate a novel space logistics paradigm, which is hereafter referred to as the interplanetary supply chain. To lay the groundwork for this anticipated paradigm shift, this work aims to introduce principles and methodologies of supply chain (SC) planning to the field of space logistics. To this end, a stochastic multistage mixed integer linear programming model is proposed that explores the vision of a permanent human presence on Mars from a logistics standpoint. The model optimizes material flows, propellant production, and in-space infrastructure allocations to identify the optimal SC network design. Notably, demand uncertainty at the Mars base is considered, which makes it the first model to investigate the effects of stochasticity in space logistics planning. Several case studies are investigated, which incorporate data on Earth–Mars transfer windows and flight trajectories obtained through the National Aeronautics and Space Administration’s trajectory browser. The results reveal numerous interdependencies and, thus, highlight the need for holistic SC modeling approaches that go beyond the isolated mission planning of the extant literature. For instance, the findings show frequent interactions among spacecraft as they regularly engage in division of labor regarding cargo and propellant transportation. Moreover, complex propellant supply networks that involve strategic in-space infrastructure allocation and propellant production on celestial bodies are established. Overall, the developed model provides valuable insights into the planning of a sustainable interplanetary travel, offers a new SC perspective, and lays the foundation for future research in this area.