Test path scheduling of digital microfluidic biochips based on combined genetic and ant colony algorithm

doi:10.13382/j.jemi.2017.08.004

Home > Archive>Volume 31, Issue 8, 2017 >1183-1191. DOI:10.13382/j.jemi.2017.08.004

Test path scheduling of digital microfluidic biochips based on combined genetic and ant colony algorithm
DOI:
                        10.13382/j.jemi.2017.08.004
                    
CSTR:
                        
                    
Author:
                        Wang JiejunWang Jiejun
1. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China; 2. Guangxi College and University Key Laboratory of Optoelectronic Information Processing, Guilin 541004, China; 3. Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin 541004, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
Liu Jiangkuan1Liu Jiangkuan
School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
Huang Xijun1Huang Xijun
School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
Xu ChuanpeiXu Chuanpei
1. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China; 3. Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin 541004, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
Mo Wei1Mo Wei
School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site

                    
Affiliation:1. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China; 2. Guangxi College and University Key Laboratory of Optoelectronic Information Processing, Guilin 541004, China; 3. Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin 541004, China
Clc Number:TP306;TN407
Fund Project:

Article

Figures

Metrics

Reference

Cited by

Materials

Comments

Abstract:

As digital microfluidic biochip is widely applied in biochemical detection fields, it is required to test the biochips completely and efficiently to guarantee the reliability of biochip. With the expansion of the size of biochip, the fault testing problem of digital microfluidic biochip is getting more and more complex. Aiming at the catastrophic faults of biochip, a test path scheduling based on combined genetic and colony algorithm is proposed to improve time efficiency of testing method. Firstly, the scheduling optimizes the conversion process of fault testing model. Then, some global excellent test paths are generated by using the global property of genetic algorithm, and the initial pheromone distribution of ant colony algorithm is formed according to these excellent test paths. Finally, the optimal test paths are searched by using ant colony algorithm. This scheduling is suitable for offline and online testing, and it can also be used for rectangle and nonrectangular biochip. The experiment results show that this scheduling can improve the efficiency of the conversion process of fault testing model. At the same time, this scheduling can improve the astringency and the time efficiency of testing algorithm in the case of getting optimized testing paths.

Key words:digital microfluidic biochips; genetic and ant colony algorithm; test path scheduling; time efficiency

Get Citation

Copy

Article Metrics

Abstract:
PDF:
HTML:
Cited by:

History

Received:
Revised:
Adopted:
Online: September 16,2017
Published:

Home

Introduction

Editorial Committee

Current Issue

Policy

Contact Us

Chinese

Get Citation

Share

Article Metrics

History

Article QR Code