粒子群优化
电磁学
计算机科学
进化计算
多群优化
计算电磁学
群体智能
数学优化
计算
群体行为
元启发式
算法
电子工程
人工智能
数学
工程类
物理
电磁场
量子力学
作者
Jacob T. Robinson,Yahya Rahmat‐Samii
标识
DOI:10.1109/tap.2004.823969
摘要
The particle swarm optimization (PSO), new to the electromagnetics community, is a robust stochastic evolutionary computation technique based on the movement and intelligence of swarms. This paper introduces a conceptual overview and detailed explanation of the PSO algorithm, as well as how it can be used for electromagnetic optimizations. This paper also presents several results illustrating the swarm behavior in a PSO algorithm developed by the authors at UCLA specifically for engineering optimizations (UCLA-PSO). Also discussed is recent progress in the development of the PSO and the special considerations needed for engineering implementation including suggestions for the selection of parameter values. Additionally, a study of boundary conditions is presented indicating the invisible wall technique outperforms absorbing and reflecting wall techniques. These concepts are then integrated into a representative example of optimization of a profiled corrugated horn antenna.
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