Antenna Optimization Using an Evolutionary Programming Algorithm with a Hybrid Mutation Operator.

Conventional implementation of evolutionary programming (EP) for continuous parameter optimization uses Gaussian mutations. However, an implementation of EP with Cauchy mutation operator has empirically been shown to outperform EP using the Gaussian mutations for optimizations of multi-modal functions with many local optima. The faster convergence of EP with Cauchy mutation has been explained in terms of the fatter tails of the Cauchy probability density function, which results in a higher probability of escaping from a local optimum. In this work we present an implementation of EP consisting of a hybrid linear combination of the Cauchy and Gaussian mutations for antenna optimization problems in order to exploit the desirable properties of these two operators. The implementation follows a procedure similar to the one described by Chellapilla (see IEEE Trans. on Evolutionary Computation, September 1998) for function optimization and uses a self-adaptive scheme for updating the standard deviation and the scale parameter of Gaussian and Cauchy distributions, respectively, during the evolution. As an example the optimization of a six-element Yagi-Uda array of dipoles using the hybrid method is presented.

Main Author: Hoorfar, Ahmad.
Other Authors: Liu, Yuan.
Language: English
Published: 2000
Online Access: http://ezproxy.villanova.edu/login?url=https://digital.library.villanova.edu/Item/vudl:176941
PID vudl:176941
id vudl:176941
modeltype_str_mv vudl-system:CoreModel
vudl-system:CollectionModel
vudl-system:ResourceCollection
datastream_str_mv DC
PARENT-QUERY
PARENT-LIST-RAW
PARENT-LIST
MEMBER-QUERY
MEMBER-LIST-RAW
LEGACY-METS
LICENSE
AGENTS
PROCESS-MD
THUMBNAIL
STRUCTMAP
RELS-EXT
hierarchytype
sequence_vudl_176907_str 0000000012
has_order_str no
hierarchy_top_id vudl:171664
hierarchy_top_title Villanova Digital Collection
hierarchy_parent_id vudl:176907
hierarchy_parent_title Hoorfar Ahmad
hierarchy_sequence 0000000012
hierarchy_first_parent_id_str vudl:176941
hierarchy_sequence_sort_str 0000000012
hierarchy_all_parents_str_mv vudl:172968
vudl:171664
vudl:176907
first_indexed 2014-01-11T22:32:44Z
last_indexed 2014-01-11T22:32:44Z
recordtype vudl
fullrecord <root> <url> http://digital.library.villanova.edu/files/vudl:176941/DC </url> <thumbnail> http://digital.library.villanova.edu/files/vudl:176941/THUMBNAIL </thumbnail> </root>
spelling
institution Villanova University
collection Digital Library
language English
dc_source_str_mv Proceedings of the Antennas and Propagation Sociey International Symposium 2, 1026-1029.
author Hoorfar, Ahmad.
author_s Hoorfar, Ahmad.
spellingShingle Hoorfar, Ahmad.
Antenna Optimization Using an Evolutionary Programming Algorithm with a Hybrid Mutation Operator.
author-letter Hoorfar, Ahmad.
author_sort_str Hoorfar, Ahmad.
author2 Liu, Yuan.
author2Str Liu, Yuan.
dc_title_str Antenna Optimization Using an Evolutionary Programming Algorithm with a Hybrid Mutation Operator.
title Antenna Optimization Using an Evolutionary Programming Algorithm with a Hybrid Mutation Operator.
title_short Antenna Optimization Using an Evolutionary Programming Algorithm with a Hybrid Mutation Operator.
title_full Antenna Optimization Using an Evolutionary Programming Algorithm with a Hybrid Mutation Operator.
title_fullStr Antenna Optimization Using an Evolutionary Programming Algorithm with a Hybrid Mutation Operator.
title_full_unstemmed Antenna Optimization Using an Evolutionary Programming Algorithm with a Hybrid Mutation Operator.
collection_title_sort_str antenna optimization using an evolutionary programming algorithm with a hybrid mutation operator.
title_sort antenna optimization using an evolutionary programming algorithm with a hybrid mutation operator.
description Conventional implementation of evolutionary programming (EP) for continuous parameter optimization uses Gaussian mutations. However, an implementation of EP with Cauchy mutation operator has empirically been shown to outperform EP using the Gaussian mutations for optimizations of multi-modal functions with many local optima. The faster convergence of EP with Cauchy mutation has been explained in terms of the fatter tails of the Cauchy probability density function, which results in a higher probability of escaping from a local optimum. In this work we present an implementation of EP consisting of a hybrid linear combination of the Cauchy and Gaussian mutations for antenna optimization problems in order to exploit the desirable properties of these two operators. The implementation follows a procedure similar to the one described by Chellapilla (see IEEE Trans. on Evolutionary Computation, September 1998) for function optimization and uses a self-adaptive scheme for updating the standard deviation and the scale parameter of Gaussian and Cauchy distributions, respectively, during the evolution. As an example the optimization of a six-element Yagi-Uda array of dipoles using the hybrid method is presented.
publishDate 2000
normalized_sort_date 2000-01-01T00:00:00Z
dc_date_str 2000
license_str protected
REPOSITORYNAME FgsRepos
REPOSBASEURL http://hades.library.villanova.edu:8088/fedora
fgs.state Active
fgs.label Antenna Optimization Using an Evolutionary Programming Algorithm with a Hybrid Mutation Operator.
fgs.ownerId diglibEditor
fgs.createdDate 2013-01-22T06:03:26.507Z
fgs.lastModifiedDate 2013-12-05T17:06:11.704Z
dc.title Antenna Optimization Using an Evolutionary Programming Algorithm with a Hybrid Mutation Operator.
dc.creator Hoorfar, Ahmad.
Liu, Yuan.
dc.description Conventional implementation of evolutionary programming (EP) for continuous parameter optimization uses Gaussian mutations. However, an implementation of EP with Cauchy mutation operator has empirically been shown to outperform EP using the Gaussian mutations for optimizations of multi-modal functions with many local optima. The faster convergence of EP with Cauchy mutation has been explained in terms of the fatter tails of the Cauchy probability density function, which results in a higher probability of escaping from a local optimum. In this work we present an implementation of EP consisting of a hybrid linear combination of the Cauchy and Gaussian mutations for antenna optimization problems in order to exploit the desirable properties of these two operators. The implementation follows a procedure similar to the one described by Chellapilla (see IEEE Trans. on Evolutionary Computation, September 1998) for function optimization and uses a self-adaptive scheme for updating the standard deviation and the scale parameter of Gaussian and Cauchy distributions, respectively, during the evolution. As an example the optimization of a six-element Yagi-Uda array of dipoles using the hybrid method is presented.
dc.date 2000
dc.identifier vudl:176941
dc.source Proceedings of the Antennas and Propagation Sociey International Symposium 2, 1026-1029.
dc.language en
license.mdRef http://digital.library.villanova.edu/copyright.html
agent.name Falvey Memorial Library, Villanova University
KHL
has_thumbnail true
THUMBNAIL_contentDigest_type MD5
THUMBNAIL_contentDigest_digest 203c69e18f4f46c81e9892448d2c07cd
THUMBNAIL_contentLocation_type INTERNAL_ID
THUMBNAIL_contentLocation_ref http://hades.library.villanova.edu:8088/fedora/get/vudl:176941/THUMBNAIL/2013-01-22T06:03:28.397Z
relsext.hasModel info:fedora/vudl-system:CoreModel
info:fedora/vudl-system:CollectionModel
info:fedora/vudl-system:ResourceCollection
relsext.itemID oai:digital.library.villanova.edu:vudl:176941
relsext.isMemberOf info:fedora/vudl:176907
relsext.hasLegacyURL http://digital.library.villanova.edu/Villanova%20Digital%20Collection/Faculty%20Fulltext/Hoorfar%20Ahmad/HoorfarAhmad-dbc3c085-5c62-43c8-b94e-e7a21695d599.xml
relsext.sortOn title
relsext.sequence vudl:176907#12
_version_ 1504168254898176000
score 13.643672
subpages