摘要
提出一种能够适应各种交通流模式的电梯群控智能优化调度方法.运用模糊神经网络对电梯的状态变量进行数据融合,融合出影响调度决策的电梯特征参数.通过小生境遗传算法对特征参数进行多目标优化分析,完成最优调度.仿真实验表明,该方法能够在各种交通流模式下进行相应的合理调度.
A new intelligent optimal dispatching method for elevator group control systems is proposed. Fuzzy neural network is adopted to fuse elevator state variables in data disposal unit. After data fusion, elevator characteristic parameters as inputs of optimal dispatching unit are gained and further optimized by multi-object optimal analysis to achieve final optimal assignment. The Niche-based genetic algorithm is used to globally optimize elevator characteristic parameters. The simulation results show that this method realizes corresponding reasonable elevator dispatching according to various traffic flow modes.
出处
《控制与决策》
EI
CSCD
北大核心
2004年第8期939-942,共4页
Control and Decision
基金
天津市自然科学基金重点资助项目(993801211).
关键词
电梯群控系统
调度方法
数据融合
小生境遗传算法
Computer simulation
Elevators
Fuzzy sets
Genetic algorithms
Global optimization
Neural networks
