This study investigates an Earth observation satellite scheduling problem for monitoring key targets’ dynamics, where each target requires two observations within a reasonable time interval. The observation profit and observation effect depend on the interval between the two observations. To define the relationship between observation profits and intervals, a new profit function is introduced. Subsequently, a mixed-integer linear programming model is formulated. Furthermore, in order to efficiently address the problem, an exact branch-and-price algorithm is proposed. To improve solution efficiency, a neighborhood search algorithm is utilized to provide initial feasible solutions. In addition, the pricing problem is solved using a bidirectional label-setting algorithm, employing dynamic ng-path relaxation. To obtain integer solutions quickly, diving heuristic and matheuristic branching strategies are presented. More specifically, the diving heuristic strategy is used to obtain a lower bound at each column generation iteration. Computational results demonstrate that the proposed branch-and-price algorithm is superior to the conventional branch-and-cut algorithm used in CPLEX software package. Furthermore, when integrating the diving heuristic and matheuristic branching strategies, computational time is drastically reduced by an average of 98.7% compared to the exact branch-and-price algorithm. The practical applicability of the proposed algorithms is further validated and assessed through a real-world case study.


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    Titel :

    Earth Observation Satellite Scheduling With Interval-Varying Profits


    Beteiligte:
    Li, Jiaojiao (Autor:in) / Zhu, Jianghan (Autor:in) / Xu, Dongyang (Autor:in) / Wang, Jianjiang (Autor:in) / Li, Zhimeng (Autor:in) / Zhang, Kunlun (Autor:in)


    Erscheinungsdatum :

    01.12.2024


    Format / Umfang :

    2787865 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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