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Approximating Time-Dependent Transition Times in Constraint Programming for an Earth Observation Mission

Authors Romain Barrault , Cédric Pralet , Gauthier Picard , Eric Sawyer

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Subject Classification

ACM Subject Classification
  • Applied computing → Operations research
  • Theory of computation → Constraint and logic programming
  • Computing methodologies → Randomized search
Keywords
  • Earth observation satellites
  • Constraint Programming
  • Large Neighborhood Search
  • Scheduling

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Abstract

A standard problem in the field of Earth observation is the scheduling of the observations of an agile satellite constellation. Given a set of end‑user requests over Points of Interest (POIs), the problem consists in selecting observations among the candidate ones, attributing each of them to a satellite, and defining the sequence of observations planned for each satellite under operational constraints. These constraints stem from the visibility windows of the POIs and from the time‑dependent maneuvers required to reorient the satellites between successive POI observations (duration of the maneuvers function depending on their start times). This paper presents how Constraint Programming (CP) can be applied to solve this combinatorial observation dispatching and scheduling problem, the objective being to maximize a sum of collected individual observation rewards. Our main focus is the search for efficient strategies to approximate time-dependent no-overlap constraints given CP solvers that only manage sequence-dependent no-overlap constraints. In particular, we introduce constant-step and variable-step time-discretization methods, together with several approximation parameters. To get actually feasible solutions, the CP model is coupled with a greedy repair strategy that takes time-dependency into account, and a Large Neighborhood Search (LNS) that post-optimizes the solutions. This CP-Repair-LNS pipeline delivers high‑quality solutions compared to a baseline LNS.

Cite As Get BibTex

Romain Barrault, Cédric Pralet, Gauthier Picard, and Eric Sawyer. Approximating Time-Dependent Transition Times in Constraint Programming for an Earth Observation Mission. In 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 379, pp. 3:1-3:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/LIPIcs.CP.2026.3

Author Details

Romain Barrault
  • DTIS, ONERA, Université de Toulouse, 31000, Toulouse, France
Cédric Pralet
  • DTIS, ONERA, Université de Toulouse, 31000, Toulouse, France
Gauthier Picard
  • DTIS, ONERA, Université de Toulouse, 31000, Toulouse, France
Eric Sawyer
  • CNES, Toulouse, France

References

  1. Valentin Antuori, Damien T Wojtowicz, and Emmanuel Hebrard. Solving the Agile Earth Observation Satellite Scheduling Problem with CP and Local Search. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025), volume 340, pages 3:1-3:22, Edimburgh, Scotland, United Kingdom, August 2025. URL: https://doi.org/10.4230/LIPIcs.CP.2025.3.
  2. Natashia Boland, Mike Hewitt, Luke Marshall, and Martin Savelsbergh. The continuous-time service network design problem. Oper. Res., 65(5):1303-1321, 2017. URL: https://doi.org/10.1287/opre.2017.1624.
  3. Sanjeeb Dash, Oktay Günlük, Andrea Lodi, and Andrea Tramontani. A time bucket formulation for the traveling salesman problem with time windows. INFORMS J. Comput., 24:132-147, 2012. URL: https://doi.org/10.1287/IJOC.1100.0432.
  4. Vu Duc Minh, Mike Hewitt, Natashia Boland, and Martin Savelsbergh. Dynamic discretization discovery for solving the time dependent traveling salesman problem with time windows. Transportation Science, page 33, January 2019. URL: https://doi.org/10.1287/trsc.2019.0911.
  5. Ander Garcia, Pieter Vansteenwegen, Olatz Arbelaitz, Wouter Souffriau, and Maria Teresa Linaza. Integrating public transportation in personalised electronic tourist guides. Computers & Operations Research, 40(3):758-774, 2013. Transport Scheduling. URL: https://doi.org/10.1016/j.cor.2011.03.020.
  6. Lei He, Xiaolu Liu, Gilbert Laporte, Yingwu Chen, and Yingguo Chen. An improved adaptive large neighborhood search algorithm for multiple agile satellites scheduling. Computers & Operations Research, 100:12-25, 2018. URL: https://doi.org/10.1016/J.COR.2018.06.020.
  7. Lei He, Mathijs Weerdt, and Neil Yorke-Smith. Time/sequence-dependent scheduling: the design and evaluation of a general purpose tabu-based adaptive large neighbourhood search algorithm. Journal of Intelligent Manufacturing, 31(4):1051-1078, 2020. URL: https://doi.org/10.1007/S10845-019-01518-4.
  8. Felipe Lagos, Natashia Boland, and Martin Savelsbergh. Dynamic discretization discovery for solving the continuous time inventory routing problem with out-and-back routes. Computers & Operations Research, 141:105686, 2022. URL: https://doi.org/10.1016/j.cor.2021.105686.
  9. Xiaolu Liu, Gilbert Laporte, Yingwu Chen, and Renjie He. An adaptive large neighborhood search metaheuristic for agile satellite scheduling with time-dependent transition time. Computers & Operations Research, 86:41-53, 2017. URL: https://doi.org/10.1016/j.cor.2017.04.006.
  10. Penélope Aguiar Melgarejo, Philippe Laborie, and Christine Solnon. A time-dependent no-overlap constraint: Application to urban delivery problems. In Laurent Michel, editor, Integration of AI and OR Techniques in Constraint Programming, pages 1-17, Cham, 2015. Springer International Publishing. URL: https://doi.org/10.1007/978-3-319-18008-3_1.
  11. Guansheng Peng, Reginald Dewil, Cédric Verbeeck, Aldy Gunawan, Lining Xing, and Pieter Vansteenwegen. Agile Earth observation satellite scheduling: An orienteering problem with time-dependent profits and travel times. Computers & Operations Research, 111:84-98, 2019. URL: https://doi.org/10.1016/j.cor.2019.05.030.
  12. Guansheng Peng, Guopeng Song, Yongming He, Jing Yu, Shang Xiang, Lining Xing, and Pieter Vansteenwegen. Solving the agile Earth observation satellite scheduling problem with time-dependent transition times. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(3):1614-1625, 2022. URL: https://doi.org/10.1109/TSMC.2020.3031738.
  13. Guansheng Peng, Guopeng Song, Lining Xing, Aldy Gunawan, and Pieter Vansteenwegen. An exact algorithm for agile Earth observation satellite scheduling with time-dependent profits. Computers & Operations Research, 120:104946, 2020. URL: https://doi.org/10.1016/j.cor.2020.104946.
  14. Cédric Pralet. Iterated maximum large neighborhood search for the traveling salesman problem with time windows and its time-dependent version. Computers & Operations Research, 150:106078, 2023. URL: https://doi.org/10.1016/j.cor.2022.106078.
  15. Samuel Squillaci, Cédric Pralet, and Stéphanie Roussel. Scheduling complex observation requests for constellation of satellites: Large neighborhood search approaches. In Integration of Constraint Programming, Artificial Intelligence, and Operations Research: 20th International Conference, CPAIOR 2023, Nice, France, May 29 –June 1, 2023, Proceedings, pages 443-459, Berlin, Heidelberg, 2023. Springer-Verlag. URL: https://doi.org/10.1007/978-3-031-33271-5_29.
  16. Samuel Squillaci, Cédric Pralet, and Stéphanie Roussel. Comparison of time-dependent and time-independent scheduling approaches for a constellation of Earth observing satellites. In 13th International Workshop on Planning and Scheduling for Space (IWPSS), 2023. Google Scholar
  17. Xinwei Wang, Guohua Wu, Lining Xing, and Witold Pedrycz. Agile Earth observation satellite scheduling over 20 years: Formulations, methods, and future directions. IEEE Systems Journal, 15(3):3881-3892, 2021. URL: https://doi.org/10.1109/JSYST.2020.2997050.
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