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This paper leverages state-of-the-art constellation reconfigurability to develop the reconfigurable EOS scheduling problem (REOSSP), wherein EOSs are assumed to be maneuverable, forming a more optimal constellation configuration at multiple opportunities during a schedule. This paper develops a novel mixed-integer linear programming formulation for the REOSSP to optimally solve the scheduling problem for given parameters. Additionally, since the REOSSP can be computationally expensive for large-scale problems, a rolling horizon procedure (RHP) solution method is developed. The performance of the REOSSP is benchmarked against the EOSSP, which serves as a baseline, through a set of random instances where problem characteristics are varied and a case study in which Hurricane Sandy is used to demonstrate realistic performance. These experiments demonstrate the value of constellation reconfigurability in its application to the EOSSP, yielding solutions that improve performance, while the RHP enhances computational runtime for large-scale REOSSP instances.<\/jats:p>","DOI":"10.2514\/1.i011659","type":"journal-article","created":{"date-parts":[[2025,11,7]],"date-time":"2025-11-07T06:45:12Z","timestamp":1762497912000},"page":"136-154","update-policy":"https:\/\/doi.org\/10.2514\/aiaa_crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["Reconfigurable Earth Observation Satellite Scheduling Problem"],"prefix":"10.2514","volume":"23","author":[{"given":"Brycen D.","family":"Pearl","sequence":"first","affiliation":[{"name":"West Virginia University"}]},{"given":"Joseph M.","family":"Miller","sequence":"additional","affiliation":[{"name":"West Virginia University"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2333-0083","authenticated-orcid":false,"given":"Hang 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