考虑服务水平的IT运维人员调度的智能遗传算法  

Intelligent Genetic Algorithm for Workforce Scheduling Considering Service Level in IT Maintenance Service

作　　者：陈芮莹 王承涛 刘振元[1,3] Chen Ruiying;Wang Chengtao;Liu Zhenyuan(School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan 430074,China;Wuhan Windoor Information Technology Company.LTD,Wuhan 430040,China;Key Laboratory of Education Ministry for Image Processing and Intelligent Control,Wuhan 430074,China)

机构地区：[1]华中科技大学人工智能与自动化学院,湖北武汉430074 [2]武汉问道信息技术有限公司,湖北武汉430040 [3]图像信息处理与智能控制教育部重点实验室,湖北武汉430074

出　　处：《系统仿真学报》2021年第3期732-744,共13页Journal of System Simulation

基　　金：国家自然科学基金(72071087);中央高校基本科研业务费(HUST:2017KFYXJJ178)。

摘　　要：在人力资源受限的情况下,针对如何在IT运维服务中使用有限的人力资源,迅速、有效地对发生的故障进行处理,建立了考虑服务水平的IT运维人员调度模型。提出了一种知识模型,设计了多种符合本问题特性的变异、交叉算子,从而形成了改进的遗传算法、基于知识模型的智能遗传算法和基于知识模型的自适应智能遗传算法。结果表明,自适应变异、交叉概率能加快解的收敛速度,知识模型能加快解的收敛速度并且提高解的优化效果。Aiming at resolving the faults quickly and effectively with limited human resource,an IT maintenance service model with the consideration of service level is proposed,A knowledge model is proposed,a variety of mutation operators and crossover operators are designed.and the improved genetic algorithm(IGA),the intelligent genetic algorithm based on knowledge model(KIGA)and the adaptive intelligent genetic algorithm based on knowledge model(KAIGA)are formed.The results show that the adaptive mutation and crossover probability can accelerate the convergence speed of the solution,and the knowledge model can also improve the optimization effect of the solution.

关 键 词：人员调度 IT运维服务 服务水平 智能遗传算法 知识模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]