Satellite observation scheduling plays a significant role in improving the efficiency of Earth observation systems. To solve the large-scale multisatellite observation scheduling problem, this article proposes an ensemble of metaheuristic and exact algorithms based on a divide-and-conquer framework (EHE-DCF), including a task allocation phase and a task scheduling phase. In the task allocation phase, each task is allocated to a proper orbit based on a metaheuristic incorporated with a probabilistic selection and a tabu mechanism derived from ant colony optimization and tabu search, respectively. In the task scheduling phase, we construct a task scheduling model for every single orbit and solve the model by using an exact method (i.e., branch and bound, B&B). The task allocation and task scheduling phases are performed iteratively to obtain a promising solution. To validate the performance of the EHE-DCF, we compare it with B&B, three divide-and-conquer-based metaheuristics, and a state-of-the-art metaheuristic. Experimental results show that the EHE-DCF can obtain higher scheduling profits and complete more tasks compared with existing algorithms. The EHE-DCF is especially efficient for large-scale satellite observation scheduling problems.


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    Titel :

    Ensemble of Metaheuristic and Exact Algorithm Based on the Divide-and-Conquer Framework for Multisatellite Observation Scheduling


    Beteiligte:
    Wu, Guohua (Autor:in) / Luo, Qizhang (Autor:in) / Du, Xiao (Autor:in) / Chen, Yingguo (Autor:in) / Suganthan, Ponnuthurai Nagaratnam (Autor:in) / Wang, Xinwei (Autor:in)


    Erscheinungsdatum :

    01.10.2022


    Format / Umfang :

    2183623 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch