摘要
随着医院高质量发展,对其垂直交通服务提出了更高要求。为了优化医院电梯群控调度系统,本文设计了基于单双层停靠和高低区分层2种控制方法下的粒子群(PSO)和GA-PSO群控调度方案。通过对医院上下行电梯在高峰期的乘客候梯、滞留、乘梯和电能消耗进行实验。结果表明,算法改进后,候梯时间、滞留时间、乘客到达率和电能消耗等指标明显优化。此外,使用SPSS平台进行马尔可夫预测分析得知未来能耗低,使得该院电梯运行实现全方位综合满意。因此,本研究的结果对医院电梯群控调度的优化具有指导和参考意义。
With the high quality development of hospitals,higher requirements are put forward for their vertical transportation services.In order to optimize the hospital elevator group control scheduling system,particle swarm optimization(PSO)and GA-PSO group control scheduling schemes based on single and double level docking and high and low level layering were designed in this study.The experimental results show that after the improvement of the algorithm,the waiting time,retention time,passenger arrival rate and electric energy consumption are obviously optimized.In addition,the use of SPSS platform for Markov prediction analysis to know the future low energy consumption,so that the hospital elevator operation to achieve comprehensive satisfaction.Therefore,the results of this study have guidance and reference significance for the optimization of hospital elevator group control scheduling.
作者
赵伊楠
王金良
袁星
吴化平
高伟翔
ZHAO Yinan;WANG Jinliang;YUAN Xing;WU Huaping;GAO Weixiang(Peking University Third Hospital,Beijing 100080,China)
出处
《中国工程机械学报》
北大核心
2025年第5期929-934,共6页
Chinese Journal of Construction Machinery
关键词
医院电梯群控调度
单双层停靠
高低区分层
GA-PSO
马尔科夫预测
hospital elevator group control dispatching
single and double berth
stratification of high and low regions
GA-PSO
markov prediction
