On-Orbit Servicing Networks in Cislunar Space: A Framework for Orbit Selection, Transfer Design, and Scheduling

Abstract This investigation introduces a comprehensive framework for designing and optimizing on-orbit servicing networks in cislunar space, integrating innovative approaches to orbit selection, transfer design, and initial scheduling. Within the context of this investigation, scheduling refers to the selection of the servicer-customer satellite pairings and the order in which each of the customer hubs are processed. A genetic algorithm serves as a basis for initial orbit selection, as well as search space reduction by adhering to beneficial criteria such as deployment costs, station-keeping requirements, and Lunar south pole coverage. The Genetic Algorithm is also leveraged to identify high-performing orbit families while supporting the extension to additional mission objectives. A phasing-informed transfer design pipeline is introduced, employing manifold arc trajectories and phasing penalties to estimate transfer costs efficiently for long-range rendezvous. This approach enhances the understanding of the underlying dynamics that is critical for trajectory design and schedule development. Two initial scheduling solutions are proposed: an Auction Algorithm with a low computational cost and a computationally intensive Genetic Algorithm. These strategies facilitate the creation of scalable servicing plans across diverse orbital configurations and a varying numbers of satellites. Trade space analysis further identifies optimal orbit configurations that align with mission requirements. This versatile and adaptable methodology offers critical insights into orbit selection, transfer trajectory design, and servicer scheduling options, delivering a robust foundation for designing servicing networks tailored to meet diverse mission objectives.