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A multi-objective local search heuristic for scheduling Earth observations taken by an agile satellite

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  • Tangpattanakul, Panwadee
  • Jozefowiez, Nicolas
  • Lopez, Pierre

Abstract

This paper presents an indicator-based multi-objective local search (IBMOLS) to solve a multi-objective optimization problem. The problem concerns the selection and scheduling of observations for an agile Earth observing satellite. The mission of an Earth observing satellite is to obtain photographs of the Earth surface to satisfy user requirements. Requests from several users have to be managed before transmitting an order, which is a sequence of selected acquisitions, to the satellite. The obtained sequence has to optimize two objectives under operation constraints. The objectives are to maximize the total profit of the selected acquisitions and simultaneously to ensure the fairness of resource sharing by minimizing the maximum profit difference between users. Experiments are conducted on realistic instances. Hypervolumes of the approximate Pareto fronts are computed and the results from IBMOLS are compared with the results from the biased random-key genetic algorithm (BRKGA).

Suggested Citation

  • Tangpattanakul, Panwadee & Jozefowiez, Nicolas & Lopez, Pierre, 2015. "A multi-objective local search heuristic for scheduling Earth observations taken by an agile satellite," European Journal of Operational Research, Elsevier, vol. 245(2), pages 542-554.
    • Handle: RePEc:eee:ejores:v:245:y:2015:i:2:p:542-554
    DOI: 10.1016/j.ejor.2015.03.011
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    References listed on IDEAS

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    Cited by:

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    2. Bernhard, Pierre & Deschamps, Marc & Zaccour, Georges, 2023. "Large satellite constellations and space debris: Exploratory analysis of strategic management of the space commons," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1140-1157.
    3. Chen, Xiaoyu & Reinelt, Gerhard & Dai, Guangming & Spitz, Andreas, 2019. "A mixed integer linear programming model for multi-satellite scheduling," European Journal of Operational Research, Elsevier, vol. 275(2), pages 694-707.
    4. Zhang Ye & Hu Xiaoxuan & Zhu Waiming & Jin Peng, 2018. "Solving the Observing and Downloading Integrated Scheduling Problem of Earth Observation Satellite with a Quantum Genetic Algorithm," Journal of Systems Science and Information, De Gruyter, vol. 6(5), pages 399-420, October.
    5. Wang, Xin-Wei & Chen, Zhen & Han, Chao, 2016. "Scheduling for single agile satellite, redundant targets problem using complex networks theory," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 125-132.
    6. Rigo, Cezar Antônio & Seman, Laio Oriel & Camponogara, Eduardo & Morsch Filho, Edemar & Bezerra, Eduardo Augusto & Munari, Pedro, 2022. "A branch-and-price algorithm for nanosatellite task scheduling to improve mission quality-of-service," European Journal of Operational Research, Elsevier, vol. 303(1), pages 168-183.

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