基于自适应多种群遗传算法的可修医疗服务备件库存优化研究

Adaptive multiple-population genetic algorithm to optimize medical repairable spare parts inventory

目的:研究医疗器械行业中可修复的医疗服务备件的库存优化问题,为医疗服务备件库存策略提供指导。方法:在METRIC(multi-echelon technique for recoverable item control)可修服务备件的单个中心仓库二级库存模型基础上,采用数学建模方法建立可修医疗服务备件库存模型,采用自适应多种群遗传算法求解该模型。以医院医疗服务备件为背景,考虑多服务备件供应商、多区域维修中心及多维修站,以年预算为约束条件,建立以年缺货期望最小为目标的二级库存优化模型,设计了该模型求解的自适应多种群遗传算法,采用Matlab工具通过数值算例说明优化模型的正确性和算法的有效性。结果:自适应多种群遗传算法结合了自适应遗传算法和多种群遗传算法的双重优点,其结果优于这2种算法,有效解决了医疗服务备件库存成本问题。结论:采用数学建模和自适应多种群遗传算法能很好地解决可修复的医疗服务备件库存优化问题,研究结果对降低医疗可修服务备件库存成本、提高物流效益具有重要指导作用。

Objective To research the inventory optimization of medical repairable spare parts and guide medical repairable spare parts inventory. Methods A medical repairable spare parts inventory model was established with mathematical modeling method and then solved with adaptive multiple-population genetic algorithm, which was based on the twoechelon model of the individual central warehouse for METRIC （multi-echelon technique for recoverable item control） repairable service spare parts. A two-echelon inventory optimization model was developed with hospital medical service spare part as the background, considerations including multiple service spare part suppliers, multi-area maintenance centers and multiple maintenance stations, annual budget as the constrained condition and minimized expected number of baekorders as the objective. An adaptive multiple-population genetic algorithm was designed for the solution of the model above. Matlab was used to prove the correctness of the optimized model and the effectiveness of the algorithm. Adaptive multiple-population genetic algorithm integrated the advantages of adaptive genetic algorithm and multiple-pop- ulation genetic algorithm, and solved the problems in the cost of medical service spare parts inventory. Concloglon Mathematical modeling and adaptive multiple-population genetic algorithm can optimize medical repairable spare parts inven- tory, and contribute to decreasing the cost of medical repairable spare parts inventory while increasing logistics efficiency. [Chinese Medical Equipment Journal, 2015,36（12） ： 1-6]