基于CS和MPLDS的作战任务与平台资源匹配方法  

Approach to Operation Task and Platform Resource Matching based on CS and MPLDS

作　　者：金义冬 杨辉华[1,2] 段鹏飞[3] 

机构地区：[1]桂林电子科技大学计算机与信息安全学院,广西桂林541004 [2]北京邮电大学自动化学院,北京100876 [3]桂林电子科技大学电子工程与自动化学院,广西桂林541004

出　　处：《计算机仿真》2017年第2期5-9,254,共6页Computer Simulation

基　　金：国家自然科学基金资助项目(21365008;61562013);广西自然科学基金资助项目(2013GXNSFBA019279);桂林电子科技大学研究生创新项目资助(GDYCSZ201474;GDYCSZ201478)

摘　　要：针对传统作战任务-平台资源匹配算法中任务优先权系数计算方法存在片面性、平台选择容易陷入局部最优、平台资源利用率不够高等不足,建立以使命完成时间最早、平台资源利用率最高为目标的数学模型,提出布谷鸟搜索(CS)和多优先级列表动态规划(MPLDS)相结合的改进算法,利用CS算法优化作战任务调度顺序、采用MPLDS算法为选定任务分配平台组资源。通过联合作战战役案例对不同算法进行仿真,结果表明改进算法能够得到更短的战役完成时间和更高的平台资源利用率,验证了算法的可行性与优越性。For the shortages of traditional algorithms for salving the problem of matching between operational tasks and platform resources, such as the means of the determining priority coefficient is one - sided, the resource utilization ratio is not high enough,the selection of platform is easy to fall into local optima,a mathematical model with the objective of both minimizing the finish time of missions and maximizing the utilization rate of platform resources is established, and its solving method by combining Cuckoo Search （CS） algorithm and Multi -Priority List Dynamic Scheduling （MPLDS） algorithm is proposed. The CS algorithm is used to optimize the scheduling order of the tasks, and the MPLDS algorithm is used to select group of platforms for tasks. Simulations are carried out for a case of joint campaign with different algorithms, and it is shown that the proposed algorithm can get shorter campaign completion and higher utilization of platform resources, so it is verified to be feasible and superior.

关 键 词：任务-平台匹配 布谷鸟搜索算法 多优先级列表 动态规划算法 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]