求解并行测试任务调度问题的ACIA  

ACIA for Solving Problem of Parallel Test Task Scheduling

作　　者：李文海 管晗 LI Wenhai;GUAN Han(Department of Scientific Research,Naval Aeronautical University,Yantai 264001,China;Graduate Student’s Brigade, Naval Aeronautical University,Yantai 264001,China)

机构地区：[1]海军航空大学科研部,山东烟台264001 [2]海军航空大学研究生管理大队,山东烟台264001

出　　处：《兵器装备工程学报》2018年第3期116-120,共5页Journal of Ordnance Equipment Engineering

基　　金：海军航空大学科研关键技术培育项目"面向信号的并行测试技术"

摘　　要：针对并行测试任务调度难,任务调度效率有待提高的问题,提出了一种自适应混沌免疫算法(ACIA)。该算法利用混沌优化理论的遍历性、随机性等优势,将混沌优化理论引入人工免疫算法的种群初始化阶段和抗体变异操作阶段,并加入自适应克隆选择算子和抗体浓度调节操作,可有效减少并行测试任务调度寻找最优解的迭代次数。用某型雷达接收机并行测试系统对该算法进行验证,仿真结果表明,与Task Scheduler-T算法和免疫克隆选择算法(ICSA)相比,该算法能够快捷地得到任务调度最优序列,且测试效率更高。An adaptive chaos immune algorithm(ACIA)is presented to tackle the parallel test tasks scheduling problem.The algorithm introduces chaos optimization theory in both the initialization phase and mutation operator of artificial immune algorithm making a good use of the ergodicity,stochastic property of chaos.At the same time,an adaptive clone selection operator and an antibody concentration adjustment are added based on the algorithm.Hence,it can induce the iteration times of parallel test task scheduling effectively.The proposed algorithm is proved in certain parallel test system for radar.Compared with the TaskScheduler-T algorithm and immune clonal selection algorithm(ICSA),the results of the simulation show that it is easier to find the optimal task scheduling sequence and more efficient.

关 键 词：人工免疫 混沌优化 并行测试 任务调度 自适应免疫算法 

分 类 号：TP202[自动化与计算机技术—检测技术与自动化装置] TJ06[自动化与计算机技术—控制科学与工程]