本文選題：全自動(dòng)酶免分析儀 + 多任務(wù)調(diào)度　； 參考：《計(jì)算機(jī)仿真》2014年06期

【摘要】：為了實(shí)現(xiàn)全自動(dòng)酶免分析儀多任務(wù)檢測時(shí)的流程優(yōu)化,合理安排多個(gè)項(xiàng)目的檢測順序,提出了一種基于遺傳算法的多任務(wù)調(diào)度方法,并對方法的原理和算法模型的建立進(jìn)行研究和設(shè)計(jì)。首先,分析全自動(dòng)酶免分析儀的多任務(wù)調(diào)度與ATSP問題的相似性,接著分析用遺傳算法解決ATSP問題的步驟,然后建立全自動(dòng)酶免分析儀的調(diào)度算法模型,最后用MATLAB程序仿真多任務(wù)檢測過程。結(jié)果表明,上述計(jì)的多任務(wù)調(diào)度方法尋優(yōu)得到的檢測順序比人工設(shè)定檢測效率提高15.04%。
[Abstract]:A multi-task scheduling method based on genetic algorithm is proposed in order to optimize the process of multi-task detection of automatic enzyme immunity analyzer and arrange the detection sequence of many items reasonably. The principle of the method and the establishment of the algorithm model are studied and designed. Firstly, the similarity between multi-task scheduling and ATSP problem of automatic enzyme immunity analyzer is analyzed, then the steps of solving ATSP problem with genetic algorithm are analyzed, and then the scheduling algorithm model of automatic enzyme immunity analyzer is established. Finally, the multitask detection process is simulated by MATLAB program. The results show that the detection order obtained by the multi-task scheduling method is 15.04 higher than that of manual setting.
【作者單位】： 北京信息科技大學(xué)光電測試技術(shù)北京市重點(diǎn)實(shí)驗(yàn)室;北京信息科技大學(xué)光電信息與儀器北京市工程研究中心;
【基金】：北京市科技專項(xiàng)資助項(xiàng)目(Z121101009212009) 北京市自然科學(xué)基金重點(diǎn)項(xiàng)目(KZ201010772032) 北京市新世紀(jì)百千萬人才工程計(jì)劃項(xiàng)目資助 北京市工程研究中心開放課題(GD2011006)
【分類號】：R318.6;TP18
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本文編號：2050553