摘要
粒子群优化PSO(Particle Swarm Optimization)因其实现容易、精度高、调整参数少、收敛速度快等优点而在解决优化问题中得到了广泛的应用。分析了惯性权值及加速度因子对粒子群算法优化性能的影响,进而提出改进粒子群算法的方法:线性或非线性动态调整惯性因子,从而有效地提高算法的搜索能力;进行了仿真实验,仿真结果表明改进后的算法在全局搜优的速率与精度方面均有明显提高。
The particle swarm optimization is widely used in optimization questions for its advantage of simply realized,high precision,small adjusted parameter and quick convergence velocity. The article analyses their influences of inertia and acceleration gene to optimization capability of particle swarm optimization and brings forward the improved means of dynamicly modulating the inertia gene which will improve the global and individual search capability. The simulation indicates that the impoved arithmetic is ob...
出处
《航空计算技术》
2010年第3期18-21,共4页
Aeronautical Computing Technique
基金
海军工程大学自然科学基金资助(HGDJJ2008024)
关键词
粒子群算法
动态惯性因子
航路规划
particle swarm optimization
dynamic inertia gene
fairway programming
