Digital Microfluidic Biochips (DMFBs) based on electro-wetting-on-dielectric (EWOD) technology are a class of lab-on-a-chip (LOC) devices. DMFBs can efficiently carry out biochemical analysis and have many advantages over the traditional laboratory system. DMFBs offer miniaturization, automation, and programmability. Resource-constrained scheduling is the first and vital step of fluidic-level synthesis of DMFBs while the other two are placement and routing of droplets. Scheduling DMFB operations is a constrained optimization problem which is NP-Complete. We propose an invasive weed optimization (IWO) algorithm based scheduling for the synthesis of DMFBs. The IWO algorithm is a nature-inspired meta-heuristic algorithm. Proposed algorithm can be used for the offline synthesis of DMFBs, where solution quality is more important than execution time. Each weed in the proposed algorithm represents a potential candidate solution for the scheduling problem. To calculate the fitness of individual weeds, we proposed an algorithm based on Heterogeneous Earliest Finish Time (HEFT), which incorporates resource binding, scheduling, and greedy module selection mechanism for bio-assay operations. Weeds (solutions) update their positions (priorities) by colonization behavior of weeds. Simulation results show that proposed IWO outperforms iterative improvement based algorithms and optimal ILP based algorithms which are existing for the offline synthesis of DMFBs.

基于电介质上电润湿（EWOD）技术的数字微流控生物芯片（DMFB）是一类芯片实验室（LOC）设备。DMFB可以有效地进行生化分析，并且比传统的实验室系统具有许多优势。DMFB提供小型化，自动化和可编程性。资源受限的调度是DMFB的流级合成的第一步，也是至关重要的一步，而其他两个是液滴的放置和路由。调度DMFB操作是NP-Complete的约束优化问题。我们提出基于入侵性杂草优化（IWO）算法的DMFB合成调度。IWO算法是自然启发式的元启发式算法。提议的算法可用于DMFB的离线综合，其中解决方案质量比执行时间更重要。所提出算法中的每个杂草都代表了调度问题的潜在候选解决方案。为了计算单个杂草的适应度，我们提出了一种基于异质最早完成时间（HEFT）的算法，该算法结合了资源绑定，调度和贪婪模块选择机制，用于生物分析操作。杂草（溶液）通过杂草的定殖行为更新其位置（优先级）。仿真结果表明，提出的IWO优于基于迭代改进的算法和基于ILP的最优算法，这些算法已存在于DMFB的离线合成中。它结合了用于生物测定操作的资源绑定，调度和贪婪模块选择机制。杂草（溶液）通过杂草的定殖行为更新其位置（优先级）。仿真结果表明，提出的IWO优于基于迭代改进的算法和基于ILP的最优算法，这些算法已存在于DMFB的离线合成中。它结合了用于生物测定操作的资源绑定，计划和贪婪模块选择机制。杂草（溶液）通过杂草的定殖行为更新其位置（优先级）。仿真结果表明，提出的IWO优于基于迭代改进的算法和基于ILP的最优算法，这些算法已存在于DMFB的离线合成中。