基于粒子群算法的自动生化分析仪调度优化

IF 1.5 Q3 AUTOMATION & CONTROL SYSTEMS IET Cybersystems and Robotics Pub Date : 2022-07-27 DOI:10.1109/CYBER55403.2022.9907708
Mingyue Zhao, M. Lin, W. Fan, Q. Xie, Bo Wang
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引用次数: 0

摘要

全自动生化免疫分析仪是临床检查诊断中经常使用的仪器,其效率非常重要。目前全自动生化分析仪大多采用固定周期算法进行调度,存在检测时间长、效率低、间歇性等问题。提出了一种基于粒子群优化(PSO)算法的调度方法。该算法采用序列编码方法,将全自动生化分析仪的调度问题近似为ATSP,建立适合全自动生化分析仪调度问题的ATSP模型,从而对全自动生化分析仪的调度进行优化。
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Scheduling Optimization of Automatic Biochemical Analyzer based on Particle Swarm Optimization
Automatic biochemical immune analyzer is often used in clinical examination and diagnosis, and its efficiency is very important. At present, most automatic biochemical analyzers use fixed period algorithm for scheduling, which has long detection time, low efficiency and intermittency. In this paper, a scheduling method based on particle swarm optimization (PSO) algorithm is proposed. The algorithm adopts sequence coding method, and approximates the scheduling problem of automatic biochemical analyzer to ATSP, and establishes ATSP model suitable for the scheduling problem of fully automatic biochemical analyzer, so as to optimize the scheduling of automatic biochemical analyzer.
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来源期刊
IET Cybersystems and Robotics
IET Cybersystems and Robotics Computer Science-Information Systems
CiteScore
3.70
自引率
0.00%
发文量
31
审稿时长
34 weeks
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