摘要
层际高峰交通是上行高峰、下行高峰与层间交通客流的融合,午饭交通就是发生在现代办公楼内的层际高峰交通之一,基于午饭时期层际高峰交通的特点,本文提出了一种利用人工免疫算法实现电梯群控制动态优化的策略．该策略采用两级优化控制,利用常规的THV算法对层站召唤分配实施局部优化,采用人工免疫算法定时对层站召唤分配实施全局优化．同单纯的THV算法相比,本文提出的组合算法将平均的系统等待时间降低了21．26%,仿真结果表明,本文提出的优化控制策略能够改善午饭时期电梯系统的服务性能,具有较好的现实意义和研究价值。
Inter-floor peak traffic is a combination of up-peak traffic, down-peak traffic and inter-floor traffic. Lunch- peak traffic is a typical pattern of vertical transportation within a modern office building. Based on the characteristics of lunch-peak traffic, a dynamic optimization strategy of elevator group control is proposed in this paper by utilizing artificial immune algorithm. This strategy has a two-level control structure. One structure is the locally optimal assignment of a hall call performed by THV algorithm; the other is the globally optimal assignment of all hall calls, which is executed periodically by artificial immune algorithm. Compared to THV algorithm, the newly proposed strategy decreased the average system waiting time by 21.26%. Simulation results demonstrated that the performance of elevator system during lunch-time is greatly improved under control of the proposed strategy in this paper.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2007年第2期177-182,共6页
Control Theory & Applications
基金
国家自然科学基金(60575006
60636004)
广州市科技局科技攻关项目(108B204017)
中山大学青年教师基金(1131100)
关键词
电梯群控制
人工免疫算法
层际高峰交通
动态优化
elevator group control
artificial immune system
inter-floor peak traffic
dynamic optimization
