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A hybrid artificial bee colony algorithm for scheduling of digital microfluidic biochip operations

机译:一种用于数字微流体生物芯片运算的调度混合人造蜂殖民地算法

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Digital microfluidic biochips (DMFBs) are designed to efficiently carry out biochemical and biomedical analysis in a miniaturized way. DMFBs offer various advantages over traditional laboratory techniques and reduces cost, and increases automation and software programmability. Scheduling of microfluidic operations is the first and essential step in the fluidic-level synthesis of DMFBs, while the other two are the module placement and droplet routing. Scheduling DMFB operations is a multiconstrained optimization problem, and the particular decision problem is NP-complete. We propose a hybrid artificial bee colony (ABC) algorithm using generalized N-point crossover (GNX) based scheduling of DMFB operations. Proposed ABC-GNX perturbs through search space, evaluates various schedules possible, and returns the best schedule among the evaluated schedules. Simple list scheduling based heuristic algorithms can explore a single schedule based on the sequence generated by the priority function. Iterative improvement based search algorithms explore the search space and evaluate more schedules, but the proposed ABC-GNX algorithm produces optimal solutions in shorter execution times. Simulation results show that the proposed ABC-GNX produces a higher number of optimal completion times and faster execution times than existing algorithms.
机译:数字微流体Biochips(DMFB)旨在以小型化方式有效地进行生化和生物医学分析。 DMFBS以传统的实验室技术提供各种优势,降低成本,并提高自动化和软件可编程性。微流体操作的调度是DMFB的流体级合成中的第一和基本步骤,而另外两个是模块放置和液滴路由。调度DMFB操作是一个多组织优化问题,并且特定的决策问题是NP-Tression。我们提出了一种使用基于DMFB操作的广义n点交叉(GNX)的调度,提出了一种混合人造蜂殖民地(ABC)算法。通过搜索空间提出ABC-GNX erturbs,评估各种时间表,并返回评估的计划中的最佳计划。简单的列表基于调度的启发式算法可以基于优先函数生成的序列来探索单个计划。基于迭代改进的搜索算法探索搜索空间并评估更多的时间表,但提出的ABC-GNX算法在更短的执行时间内产生最佳解决方案。模拟结果表明,所提出的ABC-GNX产生比现有算法更高数量的最佳完成时间和更快的执行时间。

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