Research on intelligent scheduling of unmanned laboratory inspection system based on genetic algorithms
XIAO Ming
LI Wenrui
QI Junwei
JIANG Wenbo
MA Zhaoxiang
YANG Yong
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.
Keywords：unmanned laboratory inspection systemgenetic algorithmscheduling optimization methodperform-ing fitness evaluationminimizing processing timeoptimal efficiency
Publication Date：2025-09-30
Pages：8( 58-65 )