Framework for modeling and optimization of on-orbit servicing operations under demand uncertainties

Tristan Sarton du Jonchay, Hao Chen, Onalli Gunasekara, Koki Ho

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    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.

    Original languageEnglish
    Title of host publicationAccelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2020
    StatePublished - 2020
    EventAccelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2020 - Las Vegas, United States
    Duration: 16 Nov 202019 Nov 2020

    Publication series

    NameAccelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2020

    Conference

    ConferenceAccelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2020
    Country/TerritoryUnited States
    CityLas Vegas
    Period16/11/2019/11/20

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