<?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>1405-7743</journal-id>
<journal-title><![CDATA[Ingeniería, investigación y tecnología]]></journal-title>
<abbrev-journal-title><![CDATA[Ing. invest. y tecnol.]]></abbrev-journal-title>
<issn>1405-7743</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional Autónoma de México, Facultad de Ingeniería]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-77432016000400479</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Perfiles de comportamiento numérico de los métodos de búsqueda immune network algorithm y bacterial foraging optimization algorithm en funciones benchmark]]></article-title>
<article-title xml:lang="en"><![CDATA[Performance Profiles of the Algorithms Immune Network Algorithm and Bacterial Foraging Optimization Algorithm in Benchmark Functions]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ríos-Willars]]></surname>
<given-names><![CDATA[Ernesto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Liñán-García]]></surname>
<given-names><![CDATA[Ernesto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Batres]]></surname>
<given-names><![CDATA[Rafael]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Garza-García]]></surname>
<given-names><![CDATA[Yolanda]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma de Coahuila Facultad de Ciencias Químicas Departamento de Biotecnología]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Autónoma de Coahuila Facultad de Sistemas ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Tecnológico de Monterrey Campus Cuernavaca Departamento de Ingeniería Industrial]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Universidad Autónoma de Coahuila Facultad de Ciencias Químicas Departamento de Biotecnología]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2016</year>
</pub-date>
<volume>17</volume>
<numero>4</numero>
<fpage>479</fpage>
<lpage>490</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-77432016000400479&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-77432016000400479&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-77432016000400479&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En este trabajo se reporta la aplicación del concepto de perfiles de comportamiento numérico en la comparación del desempeño numérico de los métodos Immune Network Algorithm y Bacterial Foraging Optimization en 18 funciones benchmark de optimización. Específicamente la robustez, eficiencia y el tiempo de ejecución de estos métodos se compararon en espacios de búsqueda con múltiples mínimos locales, bowl-shaped, plate-shaped, valley-shaped, steep ridges y otras conocidas funciones de optimización como styblinski-tang y beale function. Los resultados muestran que el método AiNet (Castro et al., 2002) es más robusto que el método BFOA (Passino, 2010) para los casos de estudio considerados en este trabajo. Sin embargo, existen diferencias en la eficiencia (número de funciones evaluadas y tiempo de convergencia) entre ambos métodos. Donde BFOA es el algoritmo con mejor desempeño en cuanto al número de funciones evaluadas.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract This paper reports the application of the performance profiles model comparing the numerical methods Immune Network (AiNet) and Bacterial Foraging Optimization Algorithm (BFOA) in 18 benchmark optimization functions. Specifically robustness, efficiency and execution time of these methods were compared in search spaces with local minima multiple, bowl-shaped, plate-shaped, valley-shaped, steep ridges and other known optimization functions as styblinski-tang and beale function. The results show that the method AiNet (Castro et al., 2002) is more robust than the BFOA method (Passino, 2010) for the case studies considered in this work. However there are differences in the efficiency (number of evaluated functions and convergence time) between both methods. BFOA is the algorithm with best perform in terms of the number of evaluated functions.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[perfil de comportamiento]]></kwd>
<kwd lng="es"><![CDATA[funciones benchmark]]></kwd>
<kwd lng="es"><![CDATA[AiNet]]></kwd>
<kwd lng="es"><![CDATA[BFOA]]></kwd>
<kwd lng="es"><![CDATA[optimización]]></kwd>
<kwd lng="en"><![CDATA[performance profile]]></kwd>
<kwd lng="en"><![CDATA[benchmark functions]]></kwd>
<kwd lng="en"><![CDATA[AiNet]]></kwd>
<kwd lng="en"><![CDATA[BFOA]]></kwd>
<kwd lng="en"><![CDATA[optimization]]></kwd>
</kwd-group>
</article-meta>
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