数字微流控生物芯片作为新兴的微流控技术非常适用于片上实验室的物理实现。不同于传统的逻辑和电路，数字微流控生物芯片引入了特有的概念和模式。特别的，数字微流控生物芯片面临着液滴污染、电极可靠性、以及电极缺陷等诸多可靠性问题。这给面向数字微流控生物芯片的计算机辅助设计带来了极大的挑战，在这其中有很多问题属于复杂的大规模组合优化问题，传统技术不再适用。Memetic算法是进化计算领域一类新兴优化技术，可以有效结合特定问题的启发式知识，获得较高的求解质量和求解效率。本课题针对当前数字微流控生物芯片可靠性设计中存在的若干关键问题，基于Memetic算法思想，从新的角度出发，针对试剂污染、电极可靠性、以及电极缺陷问题，研究新的数字微流控生物芯片可靠性设计方法。本课题的研究将为面向可靠性的数字微流控生物芯片的计算机辅助设计工具的开发提供重要的理论与技术准备。

Digital microfluidic biochip has been considered as a suitable candidate for lab-on-a-chip applications. Here, entirely different concepts and paradigms have to be employed which significantly differ from conventional logic and circuitry. Specifically, cross-contamination, electrode reliability, and electrode defects, decrease the system reliability of digital microfluidic biochips. Therefore, reliability-oriented design of digital microfluidic biochips has become a severe challenge faced by electronic and computer science field. Many of the design problems belong to complex large-scale combinatorial optimization problem, while the traditional design space exploration (DSE) techniques no longer apply. In recent years, as a new category of meta-heuristic algorithm framework, memetic algorithms (MAs) have achieved remarkable success in a wide range of real-world applications. MAs employ general meta-heuristics (such as genetic algorithms) as global search and problem-specific heuristic as local search. With an appropriate coordination, MAs cannot only exhibit a good explorative ability as a population-based global search algorithm does but also deliver a good exploitive performance as a local search algorithm does. This project intends to develop MA-based DSE techniques for the key issues in the reliability-oriented design of digital microfluidic biochips. This object will provide important theory and techniques for the development of reliability-oriented design tools of digital microfluidic biochips.