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针对应急条件下多星动态调度问题,建立了多目标数学规划模型,提出了应急条件多星成像任务合成策略:建立多星多轨任务合成图(MSMOTMG)模型,提出任务合成算法CP-TM。为克服合成导致任务成像机会减少的缺陷,提出了基于合成任务分解的修复技术。此外,为进一步提高调度效率,考虑了任务在等待队列中的向后移位策略,提出了综合考虑任务合成、修复和向后移位的多星动态应急调度(TMRBS-DES)算法。通过大量模拟实验,将TMRBS-DES算法同RBHA算法,以及3个baseline算法(BS-DES、TMR-DES和TMBS-DES)进行了比较。实验结果表明TMRBS-DES算法提高了调度质量,适用于应急条件下多星动态调度问题。
Aiming at the problem of multi-star dynamic scheduling under emergency conditions, a multi-objective mathematical programming model is established and a multi-star multi-satellite imaging task synthesis strategy is proposed. The MSMOTMG model is established and the task composition algorithm CP-TM is proposed. In order to overcome the defect that the synthesis leads to the reduction of the task imaging, a restoration technique based on the synthesis task decomposition is proposed. In addition, in order to further improve the scheduling efficiency, the strategy of backward shift in the queue waiting for the task is considered and a multi-star Dynamic Emergency Schedule (TMRBS-DES) algorithm considering the task synthesis, repair and backward shift is proposed. Through a large number of simulation experiments, the TMRBS-DES algorithm is compared with RBHA algorithm and three baseline algorithms (BS-DES, TMR-DES and TMBS-DES). The experimental results show that the TMRBS-DES algorithm improves the scheduling quality and is suitable for multi-star dynamic scheduling problem under emergency conditions.