<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0123-3033</journal-id>
<journal-title><![CDATA[Ingeniería y competitividad]]></journal-title>
<abbrev-journal-title><![CDATA[Ing. compet.]]></abbrev-journal-title>
<issn>0123-3033</issn>
<publisher>
<publisher-name><![CDATA[Facultad de Ingeniería, Universidad del Valle]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0123-30332021000100001</article-id>
<article-id pub-id-type="doi">10.25100/iyc.23i1.7337</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[An approximation to the use of self-adaptive genetic algorithms in weight optimization of 3-D steel trusses]]></article-title>
<article-title xml:lang="es"><![CDATA[Optimización de armaduras espaciales de acero utilizando algoritmos genéticos auto-adaptados: una primera aproximación]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ramírez-Echeverri]]></surname>
<given-names><![CDATA[Sebastián]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Villalba-Morales]]></surname>
<given-names><![CDATA[Jesús D.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Pontificia Universidad Javeriana Facultad de Ingeniería Departamento de Ingeniería Civil]]></institution>
<addr-line><![CDATA[Bogotá ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Pontificia Universidad Javeriana Facultad de Ingeniería Departamento de Ingeniería Civil]]></institution>
<addr-line><![CDATA[Bogotá ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2021</year>
</pub-date>
<volume>23</volume>
<numero>1</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0123-30332021000100001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0123-30332021000100001&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0123-30332021000100001&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract In the past few decades structural optimization through metaheuristics has gain recognition in the scientific community; non the less, to guarantee good results we require a good selection of metaheuristic&#8217;s parameters. In this paper we propose a multi-chromosome genetic algorithm with self-adaptive parameters, to optimize steel trusses in a three-dimensional space. The design variable are the sections assign to each truss element of the structure. The optimization objective is the minimize the weight of the structure, considering the displacement y maximum stress as constrains. The propose algorithm was applied to the optimization of two trusses, obtaining designs that had a 35% less weight than the initial designs and comparable to results obtained in other papers. However, the adaptation of the parameters allows a more robust optimization process when analyzing different types of trusses and eliminates the initial runs of the optimization algorithm required to calibrate the initial parameters.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En las últimas décadas, la optimización estructural mediante metaheurísticas ganó acogida en la comunidad científica; sin embargo, para garantizar buenos resultados se requiere una correcta selección de los parámetros de la metaheurísticas. En este trabajo se propone un algoritmo genético multi-cromosoma auto-adaptado para optimizar armaduras de acero tridimensionales. Las variables de diseño corresponden a las secciones asignadas a cada elemento en la armadura. El objetivo es la minimización del peso de la armadura, considerando desplazamientos y esfuerzos máximos como restricciones. El algoritmo propuesto se aplicó a la optimización de dos armaduras, produciendo diseños que pesan hasta un 35% menos que el mejor diseño inicial y son valores comparables al resultado obtenidos en otros trabajos. No obstante, la adaptación de los parámetros permite mayor robustez cuando se desea optimizar diferentes tipos de armadura y evita las ejecuciones del algoritmo de optimización que son necesarias para la calibración de sus parámetros.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Design of truss structures]]></kwd>
<kwd lng="en"><![CDATA[Genetic algorithms]]></kwd>
<kwd lng="en"><![CDATA[Parameters self-adaptation]]></kwd>
<kwd lng="en"><![CDATA[Special coding]]></kwd>
<kwd lng="en"><![CDATA[structural optimization]]></kwd>
<kwd lng="es"><![CDATA[Algoritmos genéticos]]></kwd>
<kwd lng="es"><![CDATA[Auto-adaptación de parámetros]]></kwd>
<kwd lng="es"><![CDATA[Diseño de armaduras tridimensionales]]></kwd>
<kwd lng="es"><![CDATA[Optimización de estructuras]]></kwd>
<kwd lng="es"><![CDATA[Representaciones especiales]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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