Optimization designs in patch antennas using nature-inspired metaheuristic algorithms: A review

Research output: Contribution to conferenceChapter

Abstract

In this article we present a general review of nature-inspired metaheuristic algorithms with implementations in patch antenna designs. The primary focus is on Genetic Algorithm (GA), Differential Evolution (DE), Particle Swarm Optimization (PSO), Bacterial Foraging Optimization (BFO). New algorithms recently been introduced also are analyzed, such as: Firefly algorithm (FA), Cuckoo Search (CS), Bat algorithm (BA), Social Spider Optimization (SSO) and Spider Monkey Optimization (SMO). Of each algorithm, a summary of significant examples and a flowchart for a quick and easy interpretation are presented. Finally, the common characteristics of algorithms are compared, concluding in a hierarchical classification according to the efficiency of each one to solve the patch antenna problems.

Original languageEnglish (US)
DOIs
StatePublished - 20 Feb 2019
Event2018 IEEE Biennial Congress of Argentina, ARGENCON 2018 - San Miguel de Tucuman, Argentina
Duration: 6 Jun 20188 Jun 2018

Conference

Conference2018 IEEE Biennial Congress of Argentina, ARGENCON 2018
Abbreviated titleARGENCON 2018
Country/TerritoryArgentina
CitySan Miguel de Tucuman
Period6/06/188/06/18

Keywords

  • Algorithm
  • Metaheurístic
  • Nature-Inspired
  • Optimization
  • Patch Antenna

Fingerprint

Dive into the research topics of 'Optimization designs in patch antennas using nature-inspired metaheuristic algorithms: A review'. Together they form a unique fingerprint.

Cite this