With the number of on-orbit earth observation satellites (EOSs) increases, satellite image data downlink scheduling problem is becoming the bottleneck for restricting EOSs to capture more image data. Therefore, Integrated scheduling problem for earth observation satellites is imperative, which optimizes data acquisition and data transmission simultaneously. In this paper, three different modelling frameworks, SSF, CSF and CISF, are investigated to formulate the ISPFEOS as a bi-objective optimization model along with an adaptive bi-objective memetic algorithm (ALNS + NSGA-II), which integrates the combined power of an adaptive large neighborhood search algorithm (ALNS) and a nondominated sorting genetic algorithm II (NSGA-II). In addition, two types of operators, “Destroy” operators and “Repair” operators, are designed to improve the ALNS + NSGA-II. Results of extensive computational experiments are presented which disclose that the CISF model produced superior outcomes.

随着在地地球观测卫星（EOS）数量的增加，卫星图像数据下行链路调度问题已成为限制EOS捕获更多图像数据的瓶颈。因此，对地观测卫星的综合调度问题势在必行，必须同时优化数据采集和数据传输。本文研究了三个不同的建模框架SSF，CSF和CISF，以将ISPFEOS公式化为一个双目标优化模型，以及一个结合了综合能力的自适应双目标模因算法（ALNS + NSGA-II）。自适应大邻域搜索算法（ALNS）和非支配排序遗传算法II（NSGA-II）的概述。此外，还设计了两种类型的操作员，即“销毁”操作员和“维修”操作员，以改进ALNS + NSGA-II。