数据采集与处理2012，Vol.27Issue(3)：353-357,5.
基于克隆选择算法的新型多目标派梯策略
New Multi-objective Elevator Dispatching Strategy Based on Clonal Selection Algorithm
摘要
Abstract
The pareto solution set is applied to the research of choosing weight values, and the random weight method is used. Several groups of different weight values is obtained, then the optimal Pareto solution is gained according to the elevator dispatching strategies generated by different weight values. The algorithm can provide several groups of different and optimal elevator dispatching strategies, and provide more useful data for researchers to refer. According to the advantages and disadvantages of each algorithm , gradient descent algorithm is joined with the clonal selection algorithm. The convergence rate is speeded up in later period, random balanced traffic flow between layers is defined as passengers flow, and the hybrid algorithm and the clonal selection algorithm are combined and applied to elevator group control system to find the saving energy policy. To some extent, the hybrid algorithm has much more superiority than the clonal selection algorithm.关键词
多目标优化/电梯群控/克隆选择算法/梯度下降算法/Pareto解集Key words
multi-objective optimization/ elevator group control/ clonal selection algorithm/ gradient descent algorithm/ Pareto solution set分类
信息技术与安全科学引用本文复制引用
朱盐,刘跃敏..基于克隆选择算法的新型多目标派梯策略[J].数据采集与处理,2012,27(3):353-357,5.基金项目
河南省国际科技合作(114300510029)资助项目. （114300510029）
