摘要
数字微流控生物芯片出现,使得单片并行多样品、多试剂、多生物检测量的大规模生物检测系统成为现实,需要在有限的芯片资源中优化调度各样品和试剂以减少检测时间。由于优化调度是一个NP完全问题,本文提出了以多样品检测完成时间为适应度函数,以样品和试剂混合操作类型集合为染色体,并将该染色体分别赋以一整数值代表混合操作优先级高低,同时,将染色体基因分为可同时进行混合操作而资源不冲突基因和有限任意项基因两部份,并对有限任意项基因进行移位、交叉等遗传操作,达到优化调度接近最优解。所提出算法编码基因数从(4Sm*Rn)!降低到Sm*Rn,极大改善了算法效率和并行检测所需时间。
As lots of bio-parameters can be detected in a chip at a time because of digital microfluidics-based biochips,it needs to schedule reasonably samples and regents for reducing detecting time. For optimizing scheduling is NP-complete, a near optimum solution is obtained by a new improved genetic algorithm, in which detecting time for samples is regarded as fitness function and a set of mixing types for samples and regents as chromosome represented its priority by series integers. The chromosome is separated into two sections,of which the one is for mixing operation of no resource confliction and another for limit arbitrary section that can be shifted and crossing operation. The gene number of proposed algorithm is reduced from （4Sm ＊ Rn） ! to Sm ＊ Rn and its efficiency and detecting time are improved individually.
出处
《电子器件》
CAS
2008年第4期1327-1330,共4页
Chinese Journal of Electron Devices
基金
宁波市自然科学基金资助(2007A610005)
宁波大学校基金资助(XY060048)
关键词
微流控生物芯片
微液滴
调度
Microfluidics-based Biochip
Microfluidic Droplets
Scheduling
