The Gravitational Attraction Algorithm: a New Metaheuristic Applied to Nuclear Reactor Core Design Optimization Problem
Autor(a) principal: | |
---|---|
Data de Publicação: | 2005 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional do IEN |
Texto Completo: | http://carpedien.ien.gov.br:8080/handle/ien/1695 |
Resumo: | A new metaheuristic called “Gravitational Attraction Algorithm” (GAA) is introduced in this article. It is an analogy with the gravitational force field, where a body attracts another proportionally to both masses and inversely to their distances. The GAA is a populational algorithm where, first of all, the solutions are clustered using the Fuzzy Clustering Means (FCM) algorithm. Following that, the gravitational forces of the individuals in relation to each cluster are evaluated and this individual or solution is displaced to the cluster with the greatest attractive force. Once it is inside this cluster, the solution receives small stochastic variations, performing a local exploration. Then the solutions are crossed over and the process starts all over again. The parameters required by the GAA are the “diversity factor”, which is used to create a random diversity in a fashion similar to genetic algorithm’s mutation, and the number of clusters for the FCM. GAA is applied to the reactor core design optimization problem which consists in adjusting several reactor cell parameters in order to minimize the average peak-factor in a 3-enrichment-zone reactor, considering operational restrictions. This problem was previously attacked using the canonical genetic algorithm (GA) and a Niching Genetic Algorithm (NGA). The new metaheuristic is then compared to those two algorithms. The three algorithms are submitted to the same computational effort and GAA reaches the best results, showing its potential for other applications in the nuclear engineering field as, for instance, the nuclear core reload optimization problem. |
id |
IEN_25d4099d20cca3a833e189bf3366cce8 |
---|---|
oai_identifier_str |
oai:carpedien.ien.gov.br:ien/1695 |
network_acronym_str |
IEN |
network_name_str |
Repositório Institucional do IEN |
spelling |
SACCO, Wagner FigueiredoOLIVEIRA, Cassiano R.E. dePEREIRA, Cláudio Márcio do Nascimento Abreuwagner.sacco@me.gatech.educassiano.oliveira@nre.gatech.educmnap@ien.gov.br2016-04-26T13:44:20Z2016-04-26T13:44:20Z20052005http://carpedien.ien.gov.br:8080/handle/ien/1695Submitted by Sherillyn Lopes (sherillynmartins@yahoo.com.br) on 2016-04-26T13:44:20Z No. of bitstreams: 1 The gravitational attraction algorithm a new metaheuristic.pdf: 152113 bytes, checksum: 6ddcf01957d295012876344533375341 (MD5)Made available in DSpace on 2016-04-26T13:44:20Z (GMT). No. of bitstreams: 1 The gravitational attraction algorithm a new metaheuristic.pdf: 152113 bytes, checksum: 6ddcf01957d295012876344533375341 (MD5) Previous issue date: 2005A new metaheuristic called “Gravitational Attraction Algorithm” (GAA) is introduced in this article. It is an analogy with the gravitational force field, where a body attracts another proportionally to both masses and inversely to their distances. The GAA is a populational algorithm where, first of all, the solutions are clustered using the Fuzzy Clustering Means (FCM) algorithm. Following that, the gravitational forces of the individuals in relation to each cluster are evaluated and this individual or solution is displaced to the cluster with the greatest attractive force. Once it is inside this cluster, the solution receives small stochastic variations, performing a local exploration. Then the solutions are crossed over and the process starts all over again. The parameters required by the GAA are the “diversity factor”, which is used to create a random diversity in a fashion similar to genetic algorithm’s mutation, and the number of clusters for the FCM. GAA is applied to the reactor core design optimization problem which consists in adjusting several reactor cell parameters in order to minimize the average peak-factor in a 3-enrichment-zone reactor, considering operational restrictions. This problem was previously attacked using the canonical genetic algorithm (GA) and a Niching Genetic Algorithm (NGA). The new metaheuristic is then compared to those two algorithms. The three algorithms are submitted to the same computational effort and GAA reaches the best results, showing its potential for other applications in the nuclear engineering field as, for instance, the nuclear core reload optimization problem.engInstituto de Engenharia NuclearIENBrasilMetaheuristicsGravitational Attraction AlgorithmThe Gravitational Attraction Algorithm: a New Metaheuristic Applied to Nuclear Reactor Core Design Optimization Probleminfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject2005info:eu-repo/semantics/openAccessreponame:Repositório Institucional do IENinstname:Instituto de Engenharia Nuclearinstacron:IENLICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://carpedien.ien.gov.br:8080/xmlui/bitstream/ien/1695/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52ORIGINALThe gravitational attraction algorithm a new metaheuristic.pdfThe gravitational attraction algorithm a new metaheuristic.pdfapplication/pdf152113http://carpedien.ien.gov.br:8080/xmlui/bitstream/ien/1695/1/The+gravitational+attraction+algorithm+a+new+metaheuristic.pdf6ddcf01957d295012876344533375341MD51ien/1695oai:carpedien.ien.gov.br:ien/16952016-04-26 10:44:20.079Dspace IENlsales@ien.gov.brTk9URTogUExBQ0UgWU9VUiBPV04gTElDRU5TRSBIRVJFClRoaXMgc2FtcGxlIGxpY2Vuc2UgaXMgcHJvdmlkZWQgZm9yIGluZm9ybWF0aW9uYWwgcHVycG9zZXMgb25seS4KCk5PTi1FWENMVVNJVkUgRElTVFJJQlVUSU9OIExJQ0VOU0UKCkJ5IHNpZ25pbmcgYW5kIHN1Ym1pdHRpbmcgdGhpcyBsaWNlbnNlLCB5b3UgKHRoZSBhdXRob3Iocykgb3IgY29weXJpZ2h0Cm93bmVyKSBncmFudHMgdG8gRFNwYWNlIFVuaXZlcnNpdHkgKERTVSkgdGhlIG5vbi1leGNsdXNpdmUgcmlnaHQgdG8gcmVwcm9kdWNlLAp0cmFuc2xhdGUgKGFzIGRlZmluZWQgYmVsb3cpLCBhbmQvb3IgZGlzdHJpYnV0ZSB5b3VyIHN1Ym1pc3Npb24gKGluY2x1ZGluZwp0aGUgYWJzdHJhY3QpIHdvcmxkd2lkZSBpbiBwcmludCBhbmQgZWxlY3Ryb25pYyBmb3JtYXQgYW5kIGluIGFueSBtZWRpdW0sCmluY2x1ZGluZyBidXQgbm90IGxpbWl0ZWQgdG8gYXVkaW8gb3IgdmlkZW8uCgpZb3UgYWdyZWUgdGhhdCBEU1UgbWF5LCB3aXRob3V0IGNoYW5naW5nIHRoZSBjb250ZW50LCB0cmFuc2xhdGUgdGhlCnN1Ym1pc3Npb24gdG8gYW55IG1lZGl1bSBvciBmb3JtYXQgZm9yIHRoZSBwdXJwb3NlIG9mIHByZXNlcnZhdGlvbi4KCllvdSBhbHNvIGFncmVlIHRoYXQgRFNVIG1heSBrZWVwIG1vcmUgdGhhbiBvbmUgY29weSBvZiB0aGlzIHN1Ym1pc3Npb24gZm9yCnB1cnBvc2VzIG9mIHNlY3VyaXR5LCBiYWNrLXVwIGFuZCBwcmVzZXJ2YXRpb24uCgpZb3UgcmVwcmVzZW50IHRoYXQgdGhlIHN1Ym1pc3Npb24gaXMgeW91ciBvcmlnaW5hbCB3b3JrLCBhbmQgdGhhdCB5b3UgaGF2ZQp0aGUgcmlnaHQgdG8gZ3JhbnQgdGhlIHJpZ2h0cyBjb250YWluZWQgaW4gdGhpcyBsaWNlbnNlLiBZb3UgYWxzbyByZXByZXNlbnQKdGhhdCB5b3VyIHN1Ym1pc3Npb24gZG9lcyBub3QsIHRvIHRoZSBiZXN0IG9mIHlvdXIga25vd2xlZGdlLCBpbmZyaW5nZSB1cG9uCmFueW9uZSdzIGNvcHlyaWdodC4KCklmIHRoZSBzdWJtaXNzaW9uIGNvbnRhaW5zIG1hdGVyaWFsIGZvciB3aGljaCB5b3UgZG8gbm90IGhvbGQgY29weXJpZ2h0LAp5b3UgcmVwcmVzZW50IHRoYXQgeW91IGhhdmUgb2J0YWluZWQgdGhlIHVucmVzdHJpY3RlZCBwZXJtaXNzaW9uIG9mIHRoZQpjb3B5cmlnaHQgb3duZXIgdG8gZ3JhbnQgRFNVIHRoZSByaWdodHMgcmVxdWlyZWQgYnkgdGhpcyBsaWNlbnNlLCBhbmQgdGhhdApzdWNoIHRoaXJkLXBhcnR5IG93bmVkIG1hdGVyaWFsIGlzIGNsZWFybHkgaWRlbnRpZmllZCBhbmQgYWNrbm93bGVkZ2VkCndpdGhpbiB0aGUgdGV4dCBvciBjb250ZW50IG9mIHRoZSBzdWJtaXNzaW9uLgoKSUYgVEhFIFNVQk1JU1NJT04gSVMgQkFTRUQgVVBPTiBXT1JLIFRIQVQgSEFTIEJFRU4gU1BPTlNPUkVEIE9SIFNVUFBPUlRFRApCWSBBTiBBR0VOQ1kgT1IgT1JHQU5JWkFUSU9OIE9USEVSIFRIQU4gRFNVLCBZT1UgUkVQUkVTRU5UIFRIQVQgWU9VIEhBVkUKRlVMRklMTEVEIEFOWSBSSUdIVCBPRiBSRVZJRVcgT1IgT1RIRVIgT0JMSUdBVElPTlMgUkVRVUlSRUQgQlkgU1VDSApDT05UUkFDVCBPUiBBR1JFRU1FTlQuCgpEU1Ugd2lsbCBjbGVhcmx5IGlkZW50aWZ5IHlvdXIgbmFtZShzKSBhcyB0aGUgYXV0aG9yKHMpIG9yIG93bmVyKHMpIG9mIHRoZQpzdWJtaXNzaW9uLCBhbmQgd2lsbCBub3QgbWFrZSBhbnkgYWx0ZXJhdGlvbiwgb3RoZXIgdGhhbiBhcyBhbGxvd2VkIGJ5IHRoaXMKbGljZW5zZSwgdG8geW91ciBzdWJtaXNzaW9uLgo= |
dc.title.pt_BR.fl_str_mv |
The Gravitational Attraction Algorithm: a New Metaheuristic Applied to Nuclear Reactor Core Design Optimization Problem |
title |
The Gravitational Attraction Algorithm: a New Metaheuristic Applied to Nuclear Reactor Core Design Optimization Problem |
spellingShingle |
The Gravitational Attraction Algorithm: a New Metaheuristic Applied to Nuclear Reactor Core Design Optimization Problem SACCO, Wagner Figueiredo Metaheuristics Gravitational Attraction Algorithm |
title_short |
The Gravitational Attraction Algorithm: a New Metaheuristic Applied to Nuclear Reactor Core Design Optimization Problem |
title_full |
The Gravitational Attraction Algorithm: a New Metaheuristic Applied to Nuclear Reactor Core Design Optimization Problem |
title_fullStr |
The Gravitational Attraction Algorithm: a New Metaheuristic Applied to Nuclear Reactor Core Design Optimization Problem |
title_full_unstemmed |
The Gravitational Attraction Algorithm: a New Metaheuristic Applied to Nuclear Reactor Core Design Optimization Problem |
title_sort |
The Gravitational Attraction Algorithm: a New Metaheuristic Applied to Nuclear Reactor Core Design Optimization Problem |
author |
SACCO, Wagner Figueiredo |
author_facet |
SACCO, Wagner Figueiredo OLIVEIRA, Cassiano R.E. de PEREIRA, Cláudio Márcio do Nascimento Abreu wagner.sacco@me.gatech.edu cassiano.oliveira@nre.gatech.edu cmnap@ien.gov.br |
author_role |
author |
author2 |
OLIVEIRA, Cassiano R.E. de PEREIRA, Cláudio Márcio do Nascimento Abreu wagner.sacco@me.gatech.edu cassiano.oliveira@nre.gatech.edu cmnap@ien.gov.br |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
SACCO, Wagner Figueiredo OLIVEIRA, Cassiano R.E. de PEREIRA, Cláudio Márcio do Nascimento Abreu wagner.sacco@me.gatech.edu cassiano.oliveira@nre.gatech.edu cmnap@ien.gov.br |
dc.subject.por.fl_str_mv |
Metaheuristics Gravitational Attraction Algorithm |
topic |
Metaheuristics Gravitational Attraction Algorithm |
dc.description.abstract.por.fl_txt_mv |
A new metaheuristic called “Gravitational Attraction Algorithm” (GAA) is introduced in this article. It is an analogy with the gravitational force field, where a body attracts another proportionally to both masses and inversely to their distances. The GAA is a populational algorithm where, first of all, the solutions are clustered using the Fuzzy Clustering Means (FCM) algorithm. Following that, the gravitational forces of the individuals in relation to each cluster are evaluated and this individual or solution is displaced to the cluster with the greatest attractive force. Once it is inside this cluster, the solution receives small stochastic variations, performing a local exploration. Then the solutions are crossed over and the process starts all over again. The parameters required by the GAA are the “diversity factor”, which is used to create a random diversity in a fashion similar to genetic algorithm’s mutation, and the number of clusters for the FCM. GAA is applied to the reactor core design optimization problem which consists in adjusting several reactor cell parameters in order to minimize the average peak-factor in a 3-enrichment-zone reactor, considering operational restrictions. This problem was previously attacked using the canonical genetic algorithm (GA) and a Niching Genetic Algorithm (NGA). The new metaheuristic is then compared to those two algorithms. The three algorithms are submitted to the same computational effort and GAA reaches the best results, showing its potential for other applications in the nuclear engineering field as, for instance, the nuclear core reload optimization problem. |
description |
A new metaheuristic called “Gravitational Attraction Algorithm” (GAA) is introduced in this article. It is an analogy with the gravitational force field, where a body attracts another proportionally to both masses and inversely to their distances. The GAA is a populational algorithm where, first of all, the solutions are clustered using the Fuzzy Clustering Means (FCM) algorithm. Following that, the gravitational forces of the individuals in relation to each cluster are evaluated and this individual or solution is displaced to the cluster with the greatest attractive force. Once it is inside this cluster, the solution receives small stochastic variations, performing a local exploration. Then the solutions are crossed over and the process starts all over again. The parameters required by the GAA are the “diversity factor”, which is used to create a random diversity in a fashion similar to genetic algorithm’s mutation, and the number of clusters for the FCM. GAA is applied to the reactor core design optimization problem which consists in adjusting several reactor cell parameters in order to minimize the average peak-factor in a 3-enrichment-zone reactor, considering operational restrictions. This problem was previously attacked using the canonical genetic algorithm (GA) and a Niching Genetic Algorithm (NGA). The new metaheuristic is then compared to those two algorithms. The three algorithms are submitted to the same computational effort and GAA reaches the best results, showing its potential for other applications in the nuclear engineering field as, for instance, the nuclear core reload optimization problem. |
publishDate |
2005 |
dc.date.copyright.none.fl_str_mv |
2005 |
dc.date.issued.fl_str_mv |
2005 |
dc.date.accessioned.fl_str_mv |
2016-04-26T13:44:20Z |
dc.date.available.fl_str_mv |
2016-04-26T13:44:20Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
status_str |
publishedVersion |
format |
conferenceObject |
dc.identifier.uri.fl_str_mv |
http://carpedien.ien.gov.br:8080/handle/ien/1695 |
url |
http://carpedien.ien.gov.br:8080/handle/ien/1695 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Instituto de Engenharia Nuclear |
dc.publisher.initials.fl_str_mv |
IEN |
dc.publisher.country.fl_str_mv |
Brasil |
publisher.none.fl_str_mv |
Instituto de Engenharia Nuclear |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional do IEN instname:Instituto de Engenharia Nuclear instacron:IEN |
reponame_str |
Repositório Institucional do IEN |
collection |
Repositório Institucional do IEN |
instname_str |
Instituto de Engenharia Nuclear |
instacron_str |
IEN |
institution |
IEN |
bitstream.url.fl_str_mv |
http://carpedien.ien.gov.br:8080/xmlui/bitstream/ien/1695/2/license.txt http://carpedien.ien.gov.br:8080/xmlui/bitstream/ien/1695/1/The+gravitational+attraction+algorithm+a+new+metaheuristic.pdf |
bitstream.checksum.fl_str_mv |
8a4605be74aa9ea9d79846c1fba20a33 6ddcf01957d295012876344533375341 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 |
repository.name.fl_str_mv |
Dspace IEN |
repository.mail.fl_str_mv |
lsales@ien.gov.br |
_version_ |
1656026985791488000 |