Rolling horizon optimization framework for the scheduling of on-orbit servicing operations under servicing demand uncertainties

This paper develops a framework that optimizes the operations of complex On-Orbit Servicing (OOS) infrastructures involving one or more servicers and orbital depots to provide various services to a fleet of geostationary (GEO) satellites. The proposed method uniquely combines a state-of-the-art space logistics technique with the Rolling Horizon decision making approach. The former is used to model the OOS logistical operations as a Mixed-Integer Linear Program whose globally optimal solutions can efficiently be found. The latter is used to assess the long-term value of an OOS infrastructure by accounting for the uncertain service needs that arise over time among the GEO satellites. Two case studies successfully demonstrate the effectiveness of the framework in optimizing the short- to mid-term operational scheduling and the long-term strategic planning of different OOS architectures under diverse market conditions.