摘要
随着航天科技的飞速发展,逐渐出现了由多种异构卫星组成的卫星集群。相比于传统的卫星系统,卫星集群具有规模大、平台多、载荷异构的特点,传统的卫星任务规划方法难以适用。针对卫星集群任务规划中的关键问题——面向任务的卫星Agent团队构建问题,建立了数学模型,提出了基于分支限界的精确搜索算法,并对其时间复杂度进行了分析。针对精确算法时间复杂度较高的缺点,引入了启发式剪枝机制,并按照任务集合排序策略的不同设计了3种启发式卫星团队构建算法。最后,通过多组实验分析了卫星团队构建精确搜索算法与启发式剪枝搜索算法的性能,验证了我们提出算法的有效性和实用性。
With the ongoing development of aerospace science and technology,satellite clusters consisting of many kinds of heterogeneous satellites have gradually appeared. Compared with traditional satellite systems,satellite clusters have some particular characteristics,including large-scale heterogeneous satellite platforms and various loads. It is difficult to use traditional methods to program satellite tasks. To address the problem of the formation of an agent team for task-oriented satellites,which is one of the key problems of satellite cluster task scheduling,in this study,we built a mathematical model,designed a precise searching algorithm based on branch and bound techniques,and analyzed the associated time complexity. To overcome the high time complexity that characterizes this precise algorithm,we introduced a heuristic pruning mechanism and designed three heuristic algorithms for the formation of the satellite team according to different task sequencing strategies. Finally,we conducted a series of experiments to analyze the performances of the precise search algorithm developed for the satellite team and the heuristic pruning search algorithm and demonstrated the effectiveness and practicability of both the proposed algorithms.
出处
《智能系统学报》
CSCD
北大核心
2017年第5期653-660,共8页
CAAI Transactions on Intelligent Systems
基金
国家自然科学基金项目(61101184
61174159)
