摘要
为了将微粒群优化(Particle Swarm Optimization,PSO)算法应用到离散领域,并使算法仍具有较佳的搜索性能,以信息素积累为基础,由离散状态的信息素构成微粒编码,重新构造算法的迭代公式.微粒信息素的变化基于信息素原先的情况、个体历史最优及全局历史最优.以信息素为依据进行离散状态的选择,由此提出一种基于信息素的离散PSO算法.将该方法应用于基于时延约束的最小能耗路由优化问题,能获得较好的路由优化结果,表明该算法具有优良的收敛性能.
To make particle swarm optimization algorithm with good search performance be applied to discrete domain,the particle coding is made up of the pheromones of discrete states based on the accumulation of pheromones.The iteration expressions are rebuilt.The changes of pheromones in particles are based on the original situation of pheromones,personal optimal pheromones and global optimal pheromones.The discrete states are chosen according to the pheromones.A discrete particle swarm optimization algorithm based on the pheromone is put forward.This method is applied to minimum energy routing optimization problem on the basis of delay constraints.The better routing optimization result shows that this algorithm possesses strong convergence capability.
出处
《上海海事大学学报》
北大核心
2011年第3期74-78,共5页
Journal of Shanghai Maritime University
基金
上海市优秀青年基金(ssc08022)
关键词
微粒群优化
信息素
无线传感网络
路由
particle swarm optimization
pheromone
wireless sensor network
routing
