粒子群及遗传算法在相对论返波管中的应用(英文)  

Particle Swarm Optimization and Genetic Algorithm for a Relativistic Backward Wave Oscillator

作　　者：王辉辉[1] 刘大刚[1] 蒙林[1] 刘腊群[1] 

机构地区：[1]电子科技大学物理电子学院,成都610054

出　　处：《计算物理》2014年第4期479-485,共7页Chinese Journal of Computational Physics

基　　金：Supported by the National Natural Science Foundation of China(Grant No.11175040)

摘　　要：在全三维粒子模拟软件CHIPIC平台上,分别开发了粒子群及基因算法模块.以相对论返波管为例,采用三种不同类型的参数(连续参数、离散参数、混合参数),对粒子群及基因算法进行比较.优化结果表明:粒子群算法的收敛速度更快,在有限的迭代步数内得到的目标结果也更优良,总体表现优于基因算法.Based on platform of three-dimensional particle-in-cell（ PIC）,CHIPIC,modules of particle swarm optimization（ PSO） and genetic algorithm（ GA） are designed to optimize a relativistic backward wave oscillator（ RBWO）,respectively. Comparisons of PSO and GA are implemented in three kinds of parameters of RBWO：Continuous parameter,discrete parameter,and mix parameters. It shows that performances of PSO are better than that of GA. PSO has higher optimization accuracy and convergence rate than GA.

关 键 词：粒子群优化 基因算法 相对论返波管 粒子模拟 

分 类 号：O462[理学—电子物理学]