Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design
We present an improved Pareto Genetic Algorithm (PGA), which finds solutions to problems of robust design in multi-response systems with 4 responses and as many as 10 control and 5 noise factors. Because some response values might not have been obtained in the robust design experiment and are needed...
- Autores:
-
Canessa, Enrique
Chaigneau, Sergio
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2017
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/67569
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/67569
http://bdigital.unal.edu.co/68598/
- Palabra clave:
- 62 Ingeniería y operaciones afines / Engineering
Robust design
parameter design
pareto genetic algorithm
response surface methodology
Diseño robusto
diseño de parámetros
algoritmo genético de pareto
metodología de superficie de respuesta.
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Canessa, Enriquef281d2f3-129c-44ca-965f-ea362d7ca7c0300Chaigneau, Sergioaa0bf165-1867-4e9d-8457-b650d7c8ad6f3002019-07-03T04:34:03Z2019-07-03T04:34:03Z2017-05-01ISSN: 2248-8723https://repositorio.unal.edu.co/handle/unal/67569http://bdigital.unal.edu.co/68598/We present an improved Pareto Genetic Algorithm (PGA), which finds solutions to problems of robust design in multi-response systems with 4 responses and as many as 10 control and 5 noise factors. Because some response values might not have been obtained in the robust design experiment and are needed in the search process, the PGA uses Response Surface Methodology (RSM) to estimate them. Not only the PGA delivered solutions that adequately adjusted the response means to their target values, and with low variability, but also found more Pareto efficient solutions than a previous version of the PGA. This improvement makes it easier to find solutions that meet the trade-off among variance reduction, mean adjustment and economic considerations. Furthermore, RSM allows estimating outputs’ means and variances in highly non-linear systems, making the new PGA appropriate for such systems.En este artículo se presenta un Algoritmo Genético de Pareto (AGP) mejorado que encuentra soluciones a problemas de diseño robusto en sistemas multi-respuesta con 4 respuestas y hasta 10 factores de control y 5 de ruido. Ya que algunas respuestas podrían no haber sido obtenidas en el experimento de diseño robusto y se necesitan en el proceso de búsqueda, el AGP usa metodología de superficie de respuesta (MSR) para estimarlas. El AGP no solo entregó soluciones que ajustan adecuadamente la media de las respuestas a sus valores meta y con poca variabilidad, sino que también encontró más soluciones Pareto eficientes que una versión previa del AGP. Esta mejora facilita encontrar soluciones que alcancen el balance entre reducción de variabilidad, ajuste de media y consideraciones económicas. Además, la MSR permite estimar las medias y varianzas de las respuestas de sistemas altamente no lineales, haciendo apropiado el uso del AGP en dichos sistemas.application/pdfspaUniversidad Nacional de Colombia - Sede Bogotá - Facultad de Ingenieríahttps://revistas.unal.edu.co/index.php/ingeinv/article/view/57152Universidad Nacional de Colombia Revistas electrónicas UN Ingeniería e InvestigaciónIngeniería e InvestigaciónCanessa, Enrique and Chaigneau, Sergio (2017) Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design. Ingeniería e Investigación, 37 (2). pp. 89-98. ISSN 2248-872362 Ingeniería y operaciones afines / EngineeringRobust designparameter designpareto genetic algorithmresponse surface methodologyDiseño robustodiseño de parámetrosalgoritmo genético de paretometodología de superficie de respuesta.Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter designArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL57152-344253-1-PB.pdfapplication/pdf492645https://repositorio.unal.edu.co/bitstream/unal/67569/1/57152-344253-1-PB.pdf3ee855e10e2cebe7a4ae33424022233fMD51THUMBNAIL57152-344253-1-PB.pdf.jpg57152-344253-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg8393https://repositorio.unal.edu.co/bitstream/unal/67569/2/57152-344253-1-PB.pdf.jpg44b35a42a7ab46d7e466004443241b9aMD52unal/67569oai:repositorio.unal.edu.co:unal/675692023-05-30 23:03:12.623Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |
| dc.title.spa.fl_str_mv |
Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design |
| title |
Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design |
| spellingShingle |
Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design 62 Ingeniería y operaciones afines / Engineering Robust design parameter design pareto genetic algorithm response surface methodology Diseño robusto diseño de parámetros algoritmo genético de pareto metodología de superficie de respuesta. |
| title_short |
Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design |
| title_full |
Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design |
| title_fullStr |
Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design |
| title_full_unstemmed |
Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design |
| title_sort |
Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design |
| dc.creator.fl_str_mv |
Canessa, Enrique Chaigneau, Sergio |
| dc.contributor.author.spa.fl_str_mv |
Canessa, Enrique Chaigneau, Sergio |
| dc.subject.ddc.spa.fl_str_mv |
62 Ingeniería y operaciones afines / Engineering |
| topic |
62 Ingeniería y operaciones afines / Engineering Robust design parameter design pareto genetic algorithm response surface methodology Diseño robusto diseño de parámetros algoritmo genético de pareto metodología de superficie de respuesta. |
| dc.subject.proposal.spa.fl_str_mv |
Robust design parameter design pareto genetic algorithm response surface methodology Diseño robusto diseño de parámetros algoritmo genético de pareto metodología de superficie de respuesta. |
| description |
We present an improved Pareto Genetic Algorithm (PGA), which finds solutions to problems of robust design in multi-response systems with 4 responses and as many as 10 control and 5 noise factors. Because some response values might not have been obtained in the robust design experiment and are needed in the search process, the PGA uses Response Surface Methodology (RSM) to estimate them. Not only the PGA delivered solutions that adequately adjusted the response means to their target values, and with low variability, but also found more Pareto efficient solutions than a previous version of the PGA. This improvement makes it easier to find solutions that meet the trade-off among variance reduction, mean adjustment and economic considerations. Furthermore, RSM allows estimating outputs’ means and variances in highly non-linear systems, making the new PGA appropriate for such systems. |
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2017 |
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2017-05-01 |
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2019-07-03T04:34:03Z |
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2019-07-03T04:34:03Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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info:eu-repo/semantics/article |
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http://purl.org/coar/resource_type/c_6501 |
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Text |
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ISSN: 2248-8723 |
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https://repositorio.unal.edu.co/handle/unal/67569 |
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http://bdigital.unal.edu.co/68598/ |
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ISSN: 2248-8723 |
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https://revistas.unal.edu.co/index.php/ingeinv/article/view/57152 |
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Universidad Nacional de Colombia Revistas electrónicas UN Ingeniería e Investigación Ingeniería e Investigación |
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Canessa, Enrique and Chaigneau, Sergio (2017) Response surface methodology for estimating missing values in a pareto genetic algorithm used in parameter design. Ingeniería e Investigación, 37 (2). pp. 89-98. ISSN 2248-8723 |
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Derechos reservados - Universidad Nacional de Colombia |
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Atribución-NoComercial 4.0 Internacional |
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