基于人工智能的医疗物资调度优化决策方法

Optimization decision method for medical material scheduling based on artificial intelligence

为了快速、合理地完成医疗物资的分配,并有效地提升医疗物资调度效率,提出了一种基于增强型鲸鱼算法的医疗物资调度优化方法。该方法通过改进种群初始化、位置更新策略以及预防陷入局部最优等方面,有效提高了搜索效率和全局搜索能力。在实例应用中,将该算法与粒子群算法、遗传算法以及鲸鱼算法进行了比较。实验结果表明,增强型鲸鱼算法在不同优化目标下表现优异,总成本最低达到33.02万元,总耗时最少为85.67 h。

To expedite and rationalize the allocation of medical material and effectively enhance the efficiency of medical supply scheduling,a medical supplies scheduling optimization method based on Enhanced Whale Optimization Algorithm(EWOA)is proposed.This method effectively improves search efficiency and global search capability by refining population initialization,position updating strategies,and preventing local optima.In practical applications,the algorithm is compared with Particle Swarm Optimization(PSO),Genetic Algorithm(GA),and Whale Optimization Algorithm(WOA).Experimental results demonstrate that the enhanced whale optimization algorithm performs remarkably well under different optimization objectives,with the minimum total cost reaching 33.02 million RMB and the minimum total time being 85.67 hours.