Parallel testing optimization method of digital microfluidic biochip

Abstract

A serial-parallel conversion test strategy is proposed for the test path optimization of digital microfluidic biochip which is parallelly tested by multiple droplets. It can solve the problem of the test path repetition in the partition method, as well as the droplet fluid conflict in the traditional non-partition method. Firstly, a hybrid algorithm based on priority strategy and genetic algorithm is designed to optimize the parallel test path of the biochip, so as to avoid the problem that the search process is too random when only a single intelligent algorithm is used to optimize the test path. Then an adaptive method is proposed to adjust the amount of test tasks, which can improve the average distribution method of test tasks and further optimize the parallel test of the digital microfluidic biochip. The test simulation of nine different array chips shows that the serial-parallel conversion strategy proposed in this paper is better than the partition strategy, and the experimental results show that the proposed method can improve the test efficiency of digital microfluidic biochips and reduce the test cost.