Digital microfluidic biochips (DMFBs) are attractive instruments for obtaining modern molecular biology and chemical measurements. Due to the increasingly complex measurements carried out on a DMFB, such chips are more prone to failure. To compensate for the shortcomings of the module-based DMFB, this paper proposes a routing-based fault repair method. The routing-based synthesis methodology ensures a much higher chip utilization factor by removing the virtual modules on the chip, as well as removing the extra electrodes needed as guard cells. In this paper, the routing problem is identified as a dynamic path-planning problem and mixed path design problem under certain constraints, and an improved Dijkstra and improved particle swarm optimization (ID-IPSO) algorithm is proposed. By introducing a cost function into the Dijkstra algorithm, the path-planning problem under dynamic obstacles is solved, and the problem of mixed path design is solved by redefining the position and velocity vectors of the particle swarm optimization. The ID-IPSO routing-based fault repair method is applied to a multibody fluid detection experiment. The proposed design method has a stronger optimization ability than the greedy algorithm. The algorithm is applied to , , and fault-free chips. The proposed ID-IPSO routing-based chip design method saves 13.9%, 14.3%, and 14.5% of the experiment completion time compared with the greedy algorithm. Compared with a modular fault repair method based on the genetic algorithm, the ID-IPSO routing-based fault repair method has greater advantages and can save 39.3% of the completion time on average in the completion of complex experiments. When the ratio of faulty electrodes is less than 12% and 23%, the modular and ID-IPSO routing-based fault repair methods, respectively, can guarantee a 100% failure repair rate. The utilization rate of the electrodes is 18% higher than that of the modular method, and the average electrode usage time is 17%. Therefore, the ID-IPSO routing-based fault repair method can accommodate more faulty electrodes for the same fault repair rate; the experiment completion time is shorter, the average number of electrodes is lower, and the security performance is better.

中文翻译：

---

基于改进的Dijkstra和改进的粒子群优化算法的基于路由的数字微流控生物芯片修复方法

数字微流控生物芯片（DMFB）是获得现代分子生物学和化学测量的诱人工具。由于在DMFB上进行的测量越来越复杂，因此此类芯片更​​容易出现故障。为了弥补基于模块的DMFB的缺点，提出了一种基于路由的故障修复方法。基于路由的综合方法通过去除芯片上的虚拟模块以及去除作为保护单元所需的额外电极，确保了更高的芯片利用率。在一定约束下，将路由问题识别为动态路径规划问题和混合路径设计问题，并提出了一种改进的Dijkstra算法和改进的粒子群算法（ID-IPSO）。通过将成本函数引入Dijkstra算法，解决了动态障碍下的路径规划问题，通过重新定义粒子群优化算法的位置和速度矢量，解决了混合路径设计问题。基于ID-IPSO路由的故障修复方法被应用于多体流体检测实验。所提出的设计方法比贪婪算法具有更强的优化能力。该算法适用于，和无故障芯片。与贪婪算法相比，该基于ID-IPSO路由的芯片设计方法节省了实验完成时间的13.9％，14.3％和14.5％。与基于遗传算法的模块化故障修复方法相比，基于ID-IPSO路由的故障修复方法具有更大的优势，在复杂实验的完成中平均可节省39.3％的完成时间。当故障电极的比例小于12％和23％时，模块化和基于ID-IPSO路由的故障修复方法分别可以保证100％的故障修复率。电极的利用率比模块化方法高18％，平均电极使用时间为17％。因此，基于ID-IPSO路由的故障修复方法可以在相同的故障修复率下容纳更多的故障电极。实验完成时间短，平均电极数少，安全性能更好。基于ID-IPSO路由的故障修复方法可以在相同的故障修复率下容纳更多的故障电极。实验完成时间短，平均电极数少，安全性能更好。基于ID-IPSO路由的故障修复方法可以在相同的故障修复率下容纳更多的故障电极。实验完成时间短，平均电极数少，安全性能更好。