基于免疫粒子群混合优化算法的新型派梯策略  

New Elevator Dispatching Strategy Based on Hybrid Immune Particle Swarm Optimization Algorithm

作　　者：罗飞[1] 林小兰[1] 许玉格[1] 李慧娟[1] 

机构地区：[1]华南理工大学自动化科学与工程学院,广东广州510640

出　　处：《华南理工大学学报（自然科学版）》2008年第8期1-5,共5页Journal of South China University of Technology(Natural Science Edition)

基　　金：国家自然科学基金资助项目(60774032);广东省自然科学基金资助项目(06025724);高等学校博士点专项科研基金新教师基金课题(20070561006);广州市科技攻关重点项目(2007Z2-D0121)

摘　　要：基于人工免疫优化算法和粒子群算法的优缺点可以互补的特性,提出了免疫粒子群混合优化算法,并将其应用于混合电梯群控系统中进行派梯优化.将仿真结果与人工免疫优化算法、粒子群优化算法的结果进行对比,发现免疫粒子群混合优化算法显著地提高了混合电梯群控系统的长时等待率和电梯运行量,而平均等待时间的改善不明显,说明免疫粒子群混合优化算法在优化派梯方案方面表现出良好的效果,具有优越性.According to the complementarity of the artificial immune （AI） optimization algorithm and the particle swarm optimization （PSO） algorithm, a hybrid immune particle swarm optimization algorithm is proposed and employed to optimize the elevator dispatching in the hybrid elevator-group control system. The simulated results are then compared with those obtained by AI optimization and PSO algorithms, finding that, by using the proposed algorithm, the long waiting percentage and the run count are greatly improved, while the average waiting time is not obviously shortened. It is thus concluded that the proposed algorithm is effective in optimizing the elevator dispatching in the hybrid elevator-group control system.

关 键 词：人工免疫优化算法 免疫粒子群 混合电梯群控系统 克隆选择 细胞自动机 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]