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作 者:张晶[1] 祝连庆[1,2] 王君[1] 郭阳宽[1]
机构地区:[1]北京信息科技大学光电测试技术北京市重点实验室,北京100192 [2]北京信息科技大学光电信息与仪器北京市工程研究中心,北京100192
出 处:《计算机仿真》2014年第6期321-324,389,共5页Computer Simulation
基 金:北京市科技专项资助项目(Z121101009212009);北京市自然科学基金重点项目(KZ201010772032);北京市新世纪百千万人才工程计划项目资助;北京市工程研究中心开放课题(GD2011006)
摘 要:为了实现全自动酶免分析仪多任务检测时的流程优化,合理安排多个项目的检测顺序,提出了一种基于遗传算法的多任务调度方法,并对方法的原理和算法模型的建立进行研究和设计。首先,分析全自动酶免分析仪的多任务调度与ATSP问题的相似性,接着分析用遗传算法解决ATSP问题的步骤,然后建立全自动酶免分析仪的调度算法模型,最后用MATLAB程序仿真多任务检测过程。结果表明,上述计的多任务调度方法寻优得到的检测顺序比人工设定检测效率提高15.04%。In order to realize the improvement of multitask testing for automatic enzyme immunoassay instrument and arrange the order of testing projects, a method of multitask scheduling based on genetic algorithm was proposed, and its theory and algorithm model were investigated and designed. First, the similarity of the multitask scheduling of automatic enzyme immunoassay instrument and ATSP was analyzed. Then the procedures of resolving ATSP with genetic algorithm were presented and the algorithm model of multitask scheduling was established. Finally, the process of multitask testing was simulated through designing program in MATLAB environment. Experimental results indicate that the time of the testing order through the method of multitask scheduling cost is less than the factitious order cost and the efficiency is increased by 15.04%.
分 类 号:TP301.6[自动化与计算机技术—计算机系统结构]
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