飞机再次出动保障任务优化方法

发布时间：2019-05-05 18:32

【摘要】：军用飞机的再次出动保障活动时间的长短,对飞机作战效能的发挥起到至关重要的作用。针对军用飞机在多资源约束条件下再次出动保障活动要求达到最快捷的实际军事需求,以军用飞机再次出动的部分任务为研究对象,提出了一种基于启发式优先规则与遗传算法相结合的保障任务优化新方法。首先,根据优先规则确定对任务活动次序进行优先规则编码。根据合格节点判据,实现完整的拓扑排序。然后利用遗传算法对任务需求进行初始化,根据优先规则得到的编码进行遗传算法的复制、交叉、变异。从而得到军用飞机再次出动准备的最优时间。最终通过提取军用飞机再次出动的七个任务进行了试验验证,并且将结果与人工绘制的结果进行对比。结果表明,基于启发式的遗传算法能够满足军用飞机再次出动准备时间在多资源约束条件下,时间最短,具有很高的实用价值。
[Abstract]:The length of the operation time of the military aircraft plays an important role in the operation efficiency of the aircraft. In view of the requirements of military aircraft to redeploy support activities under multi-resource constraints to achieve the fastest actual military needs, this paper takes part of the tasks of military aircraft re-deployed as the object of study. A new guarantee task optimization method based on heuristic priority rule and genetic algorithm is proposed. First of all, priority rule coding is defined according to priority rules for the order of task activities. According to the criteria of qualified nodes, complete topological ranking is realized. Then the genetic algorithm is used to initialize the task requirements, and then the genetic algorithm is duplicated, crossed, and mutated according to the code obtained by the priority rules. Thus we can get the optimal time for the military aircraft to move again. Finally, seven missions of military aircraft are extracted and verified by experiments, and the results are compared with those of manual rendering. The results show that the heuristic-based genetic algorithm can meet the requirements of military aircraft re-launch preparation time under multi-resource constraints, the shortest time, and has a high practical value.
【作者单位】： 沈阳航空航天大学自动化学院;中航工业上海航空测控技术研究所故障诊断与健康管理技术航空科技重点实验室;沈阳飞机设计研究所综合后勤保障部;
【基金】：国家自然科学基金(项目编号:51605309) 国防预研项目(项目编号:A0520110023) 国防基础科研项目(项目编号:Z052012B002) 辽宁省自然科学基金联合封闭基金(项目编号:2014024003) 航空科学基金(项目编号:20153354005)
【分类号】：E926;TP18
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本文编号：2469813