<?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>1390-6542</journal-id>
<journal-title><![CDATA[Enfoque UTE]]></journal-title>
<abbrev-journal-title><![CDATA[Enfoque UTE]]></abbrev-journal-title>
<issn>1390-6542</issn>
<publisher>
<publisher-name><![CDATA[Universidad UTE]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1390-65422015000100035</article-id>
<article-id pub-id-type="doi">10.29019/enfoqueute.v6n1.53</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[La optimización evolutiva multi objetivo en la confección de equipos de desarrollo de software: una forma de lograr la calidad en el producto final]]></article-title>
<article-title xml:lang="en"><![CDATA[Evolutionary multi-objective optimization for software development teams building: a way of obtaining quality in the final product]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Peña]]></surname>
<given-names><![CDATA[Yasnalla Rivero]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández]]></surname>
<given-names><![CDATA[Pavel Novoa]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ochoa]]></surname>
<given-names><![CDATA[Yandi Fernández]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Holguín &#8220;Oscar Lucero Moya&#8221; Facultad de Informática y Matemática ]]></institution>
<addr-line><![CDATA[Holguín ]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad de Holguín &#8220;Oscar Lucero Moya&#8221; Facultad de Informática y Matemática ]]></institution>
<addr-line><![CDATA[Holguín ]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Tecnológica Equinoccial Facultad de Ciencias de la Ingeniería Campus Santo Domingo]]></institution>
<addr-line><![CDATA[Quito ]]></addr-line>
<country>Ecuador</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2015</year>
</pub-date>
<volume>6</volume>
<numero>1</numero>
<fpage>35</fpage>
<lpage>44</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_arttext&amp;pid=S1390-65422015000100035&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_abstract&amp;pid=S1390-65422015000100035&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_pdf&amp;pid=S1390-65422015000100035&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: En la presente investigación se propone un modelo matemático que permite enfocar el proceso de creación de equipos de desarrollo de software como un problema multi objetivo discreto. Los objetivos considerados son el nivel de competencia y el nivel de utilización de los profesionales en el equipo. Dada la complejidad del espacio de búsqueda del problema, se propone la aplicación de un método de optimización aproximado. Específicamente se seleccionó el algoritmo genético NSGA-II basado en el concepto de Dominancia de Pareto. Este método fue aplicado en seis escenarios diferentes con el objetivo de analizar la calidad de soluciones que obtiene. En general se puede afirmar que el método es eficiente y obtiene soluciones (asignaciones) de alta calidad.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: In this research a mathematical model to approach the process of creating software development teams as a discrete multi-objective problem is proposed. The objectives considered are the level of competition and the level of utilization of professionals in the team. Given the complexity of the problem search space, the application of an approximate optimization method is proposed. Specifically, the genetic algorithm NSGA-II based on the concept of Pareto dominance was selected. This method was applied in six different scenarios in order to analyze the quality of the obtained solutions. In general we can say that the method is efficient and gets solutions (assignments) of high quality.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[confección de equipos]]></kwd>
<kwd lng="es"><![CDATA[optimización multiobjetivo]]></kwd>
<kwd lng="es"><![CDATA[dominancia de Pareto.]]></kwd>
<kwd lng="en"><![CDATA[team building]]></kwd>
<kwd lng="en"><![CDATA[multiobjective optimization]]></kwd>
<kwd lng="en"><![CDATA[Pareto dominance.]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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