新型PSO算法在停车场车位诱导问题中的研究  

Study of improved PSO algorithm for parking guidance

作　　者：刘子文[1] 杨恢先[1] 许翔[1] 欧训勇[2] 

机构地区：[1]湘潭大学信息工程学院,湖南湘潭411105 [2]琼州学院物理系,海南五指山572200

出　　处：《计算机工程与应用》2010年第30期233-236,共4页Computer Engineering and Applications

基　　金：海南省自然科学基金No.60897~~

摘　　要：针对现有停车场管理系统中存在的车位诱导问题,提出了一种新型的粒子群算法。该算法对粒子群算法加入交叉、变异算子,用神经网络构造适应度函数,该适应度函数描述了环境约束及路径的距离信息,该算法克服了粒子群算法在后期出现的粒子"早熟"现象。仿真结果表明了该方法的正确性和有效性。Considering the parking guidance in the management systems of large-scale parking lots,in this study,a novel approach based on particle swarm optimization is presented.The crossover and mutation operators are introduced in the PSO.The information of environment constrains and path length is integrated in the fitness function which is constructed by neural network,the advanced algorithm overcomes the limitation of particle＇s ＂prematurity＂ in the later phase of convergence.Simulation results are provided to verify the effectiveness and practicability of this approach.

关 键 词：车位诱导 路径规划 粒子群算法 神经网络 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]