基于ABC-SA混合算法的群控电梯优化调度  

Optimal Scheduling of Group-controlled Elevators Based on ABC-SA Hybrid Algorithm

作　　者：闫秀英[1] 郭普静 范凯兴 Yan Xiuying;Guo Pujing;Fan Kaixing(School of Building Services Science and Engineering,Xi'an University of Architecture andTechnology,Xi'an 710055,China;College of Architecture,Xi'an University of Architecture and Technology,Xi'an 710055,China)

机构地区：[1]西安建筑科技大学建筑设备科学与工程学院,西安710055 [2]西安建筑科技大学建筑学院,西安710055

出　　处：《计算机测量与控制》2020年第8期107-111,共5页Computer Measurement &Control

基　　金：陕西省重点研发计划项目(2017ZDXM-GY-025)。

摘　　要：为解决电梯群控系统(elevator elevator group control system,EGCS)时间和能耗性能不理想的问题,提出一种基于改进人工蜂群的电梯群控多目标优化调度算法;首先,针对EGCS控制目标复杂性,建立具有多评价指标的群控电梯调度模型,依据该模型的适应度值进行合理派梯选择;其次,引入模拟退火准则优化基本人工蜂群算法结构,以解决算法易陷入局部最优解的问题,使用混合改进的人工蜂群算法进行多目标优化调度;仿真结果表明,所提算法在侯梯时间、乘梯时间和停靠次数3个性能指标上对比基本人工蜂群算法均有所提高,有效说明该方法在求解柔性多目标群控电梯优化调度时具有一定的优越性。To solve the problem of unsatisfactory time and energy consumption of elevator group control system(EGCS),a multi-objective optimization scheduling algorithm for elevator group control based on improved artificial bee colony algorithm is proposed.Firstly,for the complexity of EGCS control target,agroup-controlled elevator dispatching model with multiple evaluation indexes is established,and reasonable elevator scheduling solution is selected according to the fitness value of the model.Then,the simulated annealing algorithm is introduced to solve the defect that the artificial bee colony algorithm is easy to fall into the local optimal solution,and it uses hybrid improved artificial bee colony algorithm for multi-objective optimal scheduling.The simulation results show that the proposed algorithm compared with the artificial bee colony algorithm on the three performance indicators of waiting time,riding time and stopping times is improved,which effectively shows that the method is effective certain advantages in solving the flexible multi-objective group-controlled elevator optimal scheduling.

关 键 词：电梯群控 多目标优化 人工蜂群 模拟退火 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]