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Genetic-A* Algorithm-Based Routing for Continuous-Flow Microfluidic Biochip in Intelligent Digital Healthcare

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Green, Pervasive, and Cloud Computing (GPC 2023)

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Abstract

In the field of intelligent digital healthcare, Continuous-flow microfluidic biochip (CFMB) has become a research direction of widespread concern. CFMB integrates a large number of microvalves and large-scale microchannel networks into a single chip, enabling efficient execution of various biochemical protocols. However, as the scale of the chip increases, the routing task for CFMB becomes increasingly complex, and traditional manual routing is no longer sufficient to meet the requirements. Therefore, this paper proposes an automatic routing framework for CFMB based on Genetic algorithm (GA) and A* algorithms. Specifically, we adopt a two-stage A* algorithm to design the routing between modules, using the routing results obtained from the A* algorithm as the basis for evaluating the quality of solutions in the GA algorithm. Then, the GA algorithm is used to search for the optimal approximate solution in the solution space. Experimental results show that this method can reduce routing length and minimize routing crossings, thereby improving the parallel transmission speed of reagents on CFMB. This approach provides a feasible solution for large-scale automated routing of CFMB in the field of intelligent digital healthcare.

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Acknowledgements

This work is supported by the fund of Fujian Province Digital Economy Alliance, the National Natural Science Foundation of China (No. U1905211), and the Natural Science Foundation of Fujian Province (No. 2020J01500).

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Authors and Affiliations

  1. College of Computer and Data Science, Fuzhou University, Fuzhou, 350116, China

    Huichang Huang, Zhongliao Yang, Jiayuan Zhong, Chen Dong & Ruishen Bao

  2. College of Computer and Cyber Security, Fujian Normal University, Fuzhou, 350007, China

    Li Xu

  3. Fujian Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou University, Fuzhou, China

    Huichang Huang, Zhongliao Yang, Jiayuan Zhong, Chen Dong & Ruishen Bao

Authors
  1. Huichang Huang
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  2. Zhongliao Yang
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  3. Jiayuan Zhong
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  4. Li Xu
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  5. Chen Dong
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  6. Ruishen Bao
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Corresponding author

Correspondence to Chen Dong .

Editor information

Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Hai Jin

  2. Harbin Engineering University, Harbin, China

    Zhiwen Yu

  3. Huazhong University of Science and Technology, Wuhan, China

    Chen Yu

  4. Shiga University, Shiga, Japan

    Xiaokang Zhou

  5. National Academy of Guo Ding Institute of Data Science, Beijing, China

    Zeguang Lu

  6. Harbin University of Science and Technology, Harbin, China

    Xianhua Song

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Huang, H., Yang, Z., Zhong, J., Xu, L., Dong, C., Bao, R. (2024). Genetic-A* Algorithm-Based Routing for Continuous-Flow Microfluidic Biochip in Intelligent Digital Healthcare. In: Jin, H., Yu, Z., Yu, C., Zhou, X., Lu, Z., Song, X. (eds) Green, Pervasive, and Cloud Computing. GPC 2023. Lecture Notes in Computer Science, vol 14504. Springer, Singapore. https://doi.org/10.1007/978-981-99-9896-8_14

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  • DOI: https://doi.org/10.1007/978-981-99-9896-8_14

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-9895-1

  • Online ISBN: 978-981-99-9896-8

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