工程电磁学中的粒子群优化:一种受自然启发的进化算法

Y. Rahmat-Sami, N. Jin
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引用次数: 18

摘要

本文介绍了加州大学洛杉矶分校天线实验室研制的粒子群优化(PSO)引擎在电磁工程中的典型应用。本文提供了PSO引擎的概念概述,该引擎适用于实数、二进制、单目标和多目标优化,并提供了五个示例来验证该算法在各种实际问题中的功能。例子包括双/多波段贴片天线、非周期天线阵列、周期结构、相关天线阵列等的设计。在大多数情况下,PSO提供的设计都是原型,从测量结果中观察到高质量的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Particle Swarm Optimization (PSO) in Engineering Electromagnetics: A Nature-Inspired Evolutionary Algorithm
This paper presents representative electromagnetic engineering applications of a particle swarm optimization (PSO) engine developed at UCLA antenna lab. The paper provides a conceptual overview of the PSO engine that accommodates real-number, binary, single-objective and multi-objective optimizations, along with five examples illustrated to validate the algorithm's functionality in a large variety of practical problems. Examples include the design of dual/multi-band patch antennas, aperiodic antenna arrays, periodic structures, correlator antenna arrays, etc. In most cases the designs provided by PSO are prototyped, with high-quality performance observed from the measurement results.
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