自动化药房多个出药单据的调度优化
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华北理工大学电气工程学院 唐山 063210

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N945.12;TP278

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河北省自然科学基金(E2019209492)项目资助


Scheduling optimization of multiple delivery documents in automated pharmacy
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School of Electrical Engineering, North China University of Technology,Tangshan 063210, China

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    摘要:

    为了提高自动化药房的出药速率,实现多个出药单据药品出库时间最短。以某医院自动化药房出药系统结构为基础,建立多个出药任务单据的时间调度模型。针对此模型设计了改进的混合鲸鱼优化算法(H-WOA)。首先对多个出药单据进行整合分组,融入了遗传算法的交叉、变异,来提高种群探索的多样性;其次引入了免疫克隆算法的抗体与抗体的亲和度判定原理,来帮助构建最佳执行序列;最后结合鲸鱼算法的包围收缩和螺旋更新机制来保证种群最终收敛于最佳鲸鱼位置。实现结果表明,以3个出药单据为例,H-WOA优化算法相比原算法和未含优化算法效率分别提高了6.11%和18.11%。在4个、5个出药单据调度优化上,具有同等的优化效果。证明改进算法具有很好的寻优能力。

    Abstract:

    In order to improve the delivery rate of automated pharmacies and realize the shortest delivery time of drugs with multiple delivery documents. Based on the structure of a hospital automated pharmacy delivery system, a time scheduling model of multiple delivery task documents is established. An improved hybrid whale optimization algorithm (H-WOA) is designed for this model. Firstly, multiple drug delivery documents are integrated and grouped, and the crossover and mutation of genetic algorithm are integrated to improve the diversity of population exploration. Secondly, the affinity determination principle of antibody and antibody of immune cloning algorithm is introduced to help construct the best execution sequence. Finally, the encirclement contraction and spiral update mechanism of the whale algorithm are combined to ensure that the population finally converges to the best whale position. The implementation results show that the efficiency of H-WOA optimization algorithm is improved by 6.11% and 18.11% respectively compared with the original algorithm and the algorithm without optimization. It has the same optimization effect on the scheduling optimization of 4 or 5 delivery documents. It is proved that the improved algorithm has good optimization ability.

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景会成,李嘉琪,王福斌,曾凯.自动化药房多个出药单据的调度优化[J].电子测量技术,2023,46(5):113-120

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  • 在线发布日期: 2024-02-22
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