On line test route optimization of digital microfluidic chip based on particle swarm optimization

doi:10.13382/j.jemi.2017.08.005

Home > Archive>Volume 31, Issue 8, 2017 >1192-1199. DOI:10.13382/j.jemi.2017.08.005

On line test route optimization of digital microfluidic chip based on particle swarm optimization
DOI:
                        10.13382/j.jemi.2017.08.005
                    
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                        Xu ChuanpeiXu Chuanpei
1. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004,China; 2. Guangxi Key Laboratory of Automatic Detection Technology and Instrument, Guilin 541004,China
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Lv YingLv Ying
1. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004,China; 2. Guangxi Key Laboratory of Automatic Detection Technology and Instrument, Guilin 541004,China
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Huang XijunHuang Xijun
1. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004,China; 2. Guangxi Key Laboratory of Automatic Detection Technology and Instrument, Guilin 541004,China
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Mo WeiMo Wei
1. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004,China; 2. Guangxi Key Laboratory of Automatic Detection Technology and Instrument, Guilin 541004,China
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Affiliation:1. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004,China; 2. Guangxi Key Laboratory of Automatic Detection Technology and Instrument, Guilin 541004,China
Clc Number:TP306
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Abstract:

The stability and safety of digital microfluidic biochip have high requirements in biochemical experiments. To ensure the accuracy of the experimental results, the chip needs to be tested.In this paper, proposed an algorithm for optimize online test route, based on particle swam optimization and the scheme established constraints path which used in the experimental process, application of exchange mechanism in test route sequence in order to satisfy the constraints in the biochemical process, in order to inproving the algorithm’s convergence speed and balance the gobal search ablity and local search ablity, this paper adjusting the inertia weight of the algorithm and set the convergence rate factor and degree of aggreation of the algorithm.Simulation experiments were carried out to select 15×15 array model, 7×11 array model, 7×7 array model for simulation experiments, the experimental results show that the method can be used for chip online testing, effectively shortening the test route, and improve the test efficiency.

Key words:digital microfluidic system; route optimization; particle swarm optimization algorithm

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Online: September 16,2017
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