Abstract

Info

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

Author(s):: ZHAO Feng; LIU Yang; CAO Feng; LI Cheng; The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, China

Keywords:: high-value medical consumables improved genetic algorithm binary encoding optimal management

Abstract:: 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.