煤质技术2025，Vol.40Issue(5)：58-65,8.DOI:10.3969/j.issn.1007-7677.2025.05.008
基于遗传算法的无人化验系统任务智能调度优化研究
Research on intelligent scheduling of unmanned laboratory inspection system based on genetic algorithms
肖明 1李文瑞 1齐军伟 1蒋文博 1马召祥 1杨勇2
作者信息
- 1. 华电国际电力股份有限公司天津开发区分公司,天津 300270
- 2. 湖南三德科技股份有限公司,湖南长沙 410205
- 折叠
摘要
Abstract
With the acceleration of the digital and intelligent process in thermal power enterprises,the unmanned la-boratory inspection system can improve the production efficiency and cost control.Due to its ability to simulate the process of biological evolution and utilize mechanisms such as natural selection,crossover and mutation to find the optimal solution among candidate solutions,genetic algorithms are suitable for handling task scheduling optimization problems in unmanned laboratory systems.he sample task processing workflow within the unmanned laboratory system was focused on,the task model and constructs a genetic algorithm framework to the optimal efficiency under ideal conditions were analyzed,the optimal efficiency under ideal conditions was analyzed in the paper,and a scheduling optimization method based on genetic algorithms was proposed too.The genetic algorithms method simulates the genet-ic mechanisms in nature,encoding laboratory tasks,performing fitness evaluation,selection,crossover and muta-tion operations.The optimal solution was searched for in the candidate solution population to find the optimal schedu-ling plan,thereby minimizing the total time for sample processing.The application in actual products has shown that this genetic algorithm can effectively solve the scheduling problems of the unmanned laboratory system and improve the efficiency of laboratory inspections.关键词
无人化验系统/遗传算法/调度优化方法/适应度评估/最小化处理时间/最佳效率Key words
unmanned laboratory inspection system/genetic algorithm/scheduling optimization method/perform-ing fitness evaluation/minimizing processing time/optimal efficiency分类
化学化工引用本文复制引用
肖明,李文瑞,齐军伟,蒋文博,马召祥,杨勇..基于遗传算法的无人化验系统任务智能调度优化研究[J].煤质技术,2025,40(5):58-65,8.
