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
Mingyue Zhao, M. Lin, W. Fan, Q. Xie, Bo Wang
{"title":"基于粒子群算法的自动生化分析仪调度优化","authors":"Mingyue Zhao, M. Lin, W. Fan, Q. Xie, Bo Wang","doi":"10.1109/CYBER55403.2022.9907708","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"116 1","pages":"1028-1031"},"PeriodicalIF":1.5000,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scheduling Optimization of Automatic Biochemical Analyzer based on Particle Swarm Optimization\",\"authors\":\"Mingyue Zhao, M. Lin, W. Fan, Q. Xie, Bo Wang\",\"doi\":\"10.1109/CYBER55403.2022.9907708\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":34110,\"journal\":{\"name\":\"IET Cybersystems and Robotics\",\"volume\":\"116 1\",\"pages\":\"1028-1031\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2022-07-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Cybersystems and Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CYBER55403.2022.9907708\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Cybersystems and Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CYBER55403.2022.9907708","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信