A mixed integer linear programming model for multi-satellite scheduling

• Verfasst von: Chen, Xiaoyu [VerfasserIn]
• Verfasst von: Reinelt, Gerhard [VerfasserIn]
• Verfasst von: Spitz, Andreas [VerfasserIn]
• Titel: A mixed integer linear programming model for multi-satellite scheduling
• Verf.angabe: Xiaoyu Chen, Gerhard Reinelt, Guangming Dai, Andreas Spitz
• Jahr: 2019
• Jahr des Originals: 2018
• Umfang: 14 S.
• Fussnoten: Available online 26 November 2018 ; Gesehen am 01.08.2019
• Titel Quelle: Enthalten in: European journal of operational research
• Ort Quelle: Amsterdam [u.a.] : Elsevier, 1977
• Jahr Quelle: 2019
• Band/Heft Quelle: 275(2019), 2, Seite 694-707
• ISSN Quelle: 0377-2217
• DOI: doi:10.1016/j.ejor.2018.11.058
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Earth observing satellites
• Sach-SW: Integer programming
• Sach-SW: Mathematical programming
• Sach-SW: Scheduling
• K10plus-PPN: 167046508X

Abstract

We address the multi-satellite scheduling problem with limited observation capacities that arises from the need to observe a set of targets on the Earth’s surface using imaging resources installed on a set of satellites. We define and analyze the conflict indicators of all available visible time windows of missions, as well as the feasible time intervals of resources. The problem is then formulated as a mixed integer linear programming model, in which constraints are derived from a careful analysis of the interdependency between feasible time intervals that are eligible for observations. We apply the proposed model to several different problem instances that reflect real-world situations. The computational results verify that our approach is effective for obtaining optimum solutions or solutions with a very good quality.