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一种用于连续流微流控生物芯片的路径驱动流体路由与调度方法及延迟时间优化

A Path-Driven Fluid Routing and Scheduling Method for Continuous-Flow Microfluidic Biochips with Delay Time Optimization.

作者信息

Chen Zhisheng, Liu Bowen, Su Hongjin, Chen Zhen, Liu Genggeng, Huang Xing

机构信息

School of Informatics, Xiamen University, Xiamen 361004, China.

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

出版信息

Micromachines (Basel). 2025 May 26;16(6):625. doi: 10.3390/mi16060625.

Abstract

Routing and application mapping are critical stages in the design of continuous-flow microfluidic biochips (CFMBs). The routing stage determines the channel network connecting components and ports, while application mapping schedules fluid transportation and wash operations based on the designed biochip architecture. Existing methods typically handle these stages separately: routing focuses solely on physical metrics without considering subsequent scheduling requirements, while application mapping adopts one-shot scheduling strategies that can lead to suboptimal solutions. This paper proposes an integrated path-driven methodology that jointly optimizes routing and application mapping. For routing, we develop a hybrid particle swarm optimization algorithm that incorporates conflict awareness and channel utilization strategies. For application mapping, we introduce an iterative approach that leverages historical scheduling information to progressively optimize fluidic-handling and wash operations. Experimental results on both real and synthetic benchmarks demonstrate significant improvements over state-of-the-art methods, achieving reductions of 22.05% in total channel length, 21.79% in intersections, 21.97% in total delay time, and 8.30% in biochemical reaction completion time. The proposed methodology provides an effective solution for the automated design of CFMBs with enhanced physical and operational efficiency.

摘要

路由和应用映射是连续流微流控生物芯片(CFMB)设计中的关键阶段。路由阶段确定连接组件和端口的通道网络,而应用映射则根据设计的生物芯片架构安排流体传输和清洗操作。现有方法通常分别处理这些阶段:路由仅关注物理指标,而不考虑后续的调度要求,而应用映射则采用一次性调度策略,这可能导致次优解决方案。本文提出了一种集成的路径驱动方法,该方法联合优化路由和应用映射。对于路由,我们开发了一种结合冲突感知和通道利用策略的混合粒子群优化算法。对于应用映射,我们引入了一种迭代方法,该方法利用历史调度信息逐步优化流体处理和清洗操作。在真实和合成基准上的实验结果表明,与现有方法相比有显著改进,总通道长度减少了22.05%,交叉点减少了21.79%,总延迟时间减少了21.97%,生化反应完成时间减少了8.30%。所提出的方法为具有更高物理和操作效率的CFMB自动化设计提供了一种有效解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5837/12195421/a7f253a1b1f9/micromachines-16-00625-g001.jpg

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