基于免疫算法的午饭时期层际高峰交通电梯群控制的动态优化

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。

Dynamic optimization of elevator group control based on artificial immune algorithm for inter-floor peak traffic during lunch-time

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.