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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation
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Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation

机译:面向任务的卫星集群代理团队形成的精确启发式方法

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摘要

With the development of aerospace science and technology, Earth Observation Satellite cluster which consists of heterogeneous satellites with many kinds of payloads appears gradually. Compared with the traditional satellite systems, satellite cluster has some particular characteristics, such as large-scale, heterogeneous satellite platforms, various payloads, and the capacity of performing all the observation tasks. How to select a subset from satellite cluster to perform all observation tasks effectively with low cost is a new challenge arousing in the field of aerospace resource scheduling. This is the agent team formation problem for observation task-oriented satellite cluster. A mathematical scheduling model is built. Three novel algorithms, i.e., complete search algorithm, heuristic search algorithm, and swarm intelligence optimization algorithm, are proposed to solve the problem in different scales. Finally, some experiments are conducted to validate the effectiveness and practicability of our algorithms.
机译:随着航空科学技术的发展,由具有多种有效载荷的异构卫星组成的对地观测卫星簇逐渐出现。与传统的卫星系统相比,卫星集群具有一些特殊的特征,例如大规模,异构的卫星平台,各种有效载荷以及执行所有观测任务的能力。如何从卫星集群中选择一个子集以低成本有效地执行所有观测任务,是航空航天资源调度领域的一个新挑战。这是面向观测任务的卫星集群的特工团队组成问题。建立了数学调度模型。提出了三种新颖的算法,即完全搜索算法,启发式搜索算法和群体智能优化算法,以解决不同规模的问题。最后,进行了一些实验以验证我们算法的有效性和实用性。

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