基于改进遗传算法的高值医疗设备优化管理方法  

Optimal management for high-value medical consumables based on improved genetic algorithm

作　　者：赵锋[1] 刘阳[1] 曹凤[1] 李丞[1] ZHAO Feng;LIU Yang;CAO Feng;LI Cheng(The First Affiliated Hospital of Xinjiang Medical University,Urumqi 830054,China)

机构地区：[1]新疆医科大学第一附属医院,新疆乌鲁木齐830054

出　　处：《中国医学物理学杂志》2023年第10期1291-1294,共4页Chinese Journal of Medical Physics

基　　金：新疆维吾尔自治区自然科学基金(2020D01C249);省部共建中亚高发病因与防治国家重点实验室开放课题基金(SKL-HIDCA-2022-44;SKL-HIDCA-2021-26)。

摘　　要：提出了一种基于改进遗传算法的高值医疗设备优化管理方法。根据高值医疗设备优化管理的目标随机生成一组初始解,根据个体的适应度值选择父代个体,采用二进制编码的方式结合遗传算子逐步改进种群适应度,充分发挥遗传算法的寻优能力。将所提方法应用到某医院高值医疗设备管理数据集中,结果表明基于改进遗传算法优化高值医疗设备管理的方法能够有效地降低管理成本,且明显优于粒子群算法与模拟退火算法,验证了所提出方法的有效性。A method based on improved genetic algorithm is presented to optimize high-value medical consumables management.A set of initial solutions are randomly generated according to the goal of optimal management of high-value medical consumables,and the parent individuals are selected according to the fitness value of the individual.The population fitness is gradually improved by combining the binary coding method and the genetic operator,so as to give full play to the optimization ability of the genetic algorithm.The proposed method is applied to the dataset of high-value medical consumables management in a hospital.The experimental results show that the method of optimizing high-value medical consumables management based on improved genetic algorithm effectively reduces management cost,and outperforms particle swarm algorithm and simulated annealing algorithm,which verifies its effectiveness.

关 键 词：高值医疗设备 改进遗传算法 二进制编码 优化管理 

分 类 号：R197[医药卫生—卫生事业管理] R318[医药卫生—公共卫生与预防医学]