连续微流控生物芯片(Continuous-Flow Microfluidic Biochips, CFMBs)因具有高精度、低试剂消耗和高可靠性,已广泛应用于各类生物、化学分析实验。CFMBs由流层和控制层两部分组成,其中控制层为实现复杂的控制逻辑需依赖大量片外压力控制器,因此采用多路复用器以较少数量的控制引脚进行逻辑控制。然而,现有相关工作在多路复用器的物理设计,尤其是控制阀门布局与通道布线的协同优化方面,尚未开展系统研究。为此,提出了一种基于离散粒子群优化的多路复用器布局布线协同优化方法。首先,通过阀门信息预处理限定控制阀门的可布局区域从而避免不合法布局、以提升布线可行性; 其次,采用离散粒子群优化算法构建协同优化框架,将控制阀门布局编码为粒子位置,利用内嵌A*算法的布线代价作为适应度值反馈,从而建立布局与布线的闭环反馈机制;最后,引入X结构布线方式以扩展布线解空间,进一步压缩控制通道长度。实验结果表明,所提算法在多个基准测试中表现优异,控制通道平均长度缩短了8.27%,相比传统R型布线,采用的X结构布线方式平均缩短了5.01%的通道长度,有效提升了控制阀门布局质量与控制通道布线效率。

Continuous-flow microfluidic biochips (CFMBs) are widely used in biochemical analysis due to their high precision and reliability. CFMBs consist of a flow layer and a control layer. To manage complex logic in the control layer with limited control pins, multiplexers are extensively employed. However, the physical design of multiplexers-specifically the co-optimization of valve placement and channel routing-remains underexplored. To address this, this paper proposes a co-optimization method based on Discrete Particle Swarm Optimization (DPSO). First, valve placement regions are constrained via preprocessing to ensure routing feasibility. Second, a DPSO framework encodes placement into particle positions and utilizes an embedded A* router to provide routing cost as fitness, establishing a closed-loop feedback mechanism between placement and routing. Third, X-architecture routing is introduced to expand the solution space and minimize wirelength. Experimental results demonstrate that the proposed method reduces the average control channel length by 8.27%. Notably, the X-architecture contributes a 5.01% improvement over traditional R-type routing, significantly enhancing both layout quality and routing efficiency.