火力与指挥控制2011，Vol.36Issue(6)：85-88,4.
基本粒子群算法和遗传算法用于航路规划的比较
Comparison between Particle Swarm Optimization and Genetic Algorithm for Route Planning
摘要
Abstract
There are two primary matters for optimization question one of which is looking for the entire minimal point and the other is speedy convergence velocity. As heuristic and intelligent algorithm, the genetic algorithm and particle swarm optimization are widely used in route planning for their favorable search capability. The article analyse each characteristic and mutual similarities and differences for the two algorithm and simulation is prosecuted in same campaign environment and threat space, which indicate that the particle swarm optimization is excelled than genetic algorithm in search velocity and convergence capability.关键词
粒子群算法；遗传算法；威胁概率Key words
particle swarm algorithm,genetic algorithm,threat probability分类
航空航天引用本文复制引用
汲万峰,姜礼平,朱建冲,孙钧正..基本粒子群算法和遗传算法用于航路规划的比较[J].火力与指挥控制,2011,36(6):85-88,4.基金项目
海军工程大学自然科学基金资助项目(HGDJJ2008024) （HGDJJ2008024）
