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Improved Genetic Algorithm with Local Search for Satellite Range Scheduling System and its Application in Environmental monitoring

机译：改进的局部搜索遗传算法在卫星测距系统中的应用及其在环境监测中的应用

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Satellites play an important role in such areas as environmental monitoring and disaster prediction that are related to human survival and development. Satellite monitoring and control is the key to the satellite's management and control of the ground to ensure its smooth implementation. Because of the imbalance of demand and available resources, satellite range scheduling has become particularly important. This paper analyzes the satellite range scheduling problem and sets up mathematical models and constraints. Afterwards, this paper proposes an efficient algorithm that combines improved genetic algorithm and local search method. The improved genetic algorithm is used to rapidly improve the quality of the planning scheme, and the neighborhood search is used for the subsequent small-scale optimization. In order to improve the speed of search, our algorithm uses a reorganization operation and a mutation operation adjusted with the number of iterations. In order to test the effectiveness of the algorithm, we conducted experimental verifications of the calculations of various types of satellites at different mission scales and compared them with other algorithms. (C) 2018 Elsevier Inc. All rights reserved.
机译：卫星在与人类生存和发展有关的环境监测和灾害预测等领域中发挥着重要作用。卫星监测和控制是确保地面顺利实施的卫星地面管理和控制的关键。由于需求和可用资源的不平衡，卫星测距调度变得尤为重要。本文分析了卫星测距调度问题，并建立了数学模型和约束条件。然后，提出了一种结合改进的遗传算法和局部搜索方法的高效算法。改进的遗传算法用于快速提高规划方案的质量，邻域搜索用于后续的小规模优化。为了提高搜索速度，我们的算法使用了经过迭代次数调整的重组操作和变异操作。为了测试该算法的有效性，我们对不同任务规模的各种类型卫星的计算进行了实验验证，并将其与其他算法进行了比较。 （C）2018 Elsevier Inc.保留所有权利。

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