<?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>1409-2433</journal-id>
<journal-title><![CDATA[Revista de Matemática Teoría y Aplicaciones]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. Mat]]></abbrev-journal-title>
<issn>1409-2433</issn>
<publisher>
<publisher-name><![CDATA[Centro de Investigaciones en Matemática Pura y Aplicada (CIMPA) y Escuela de Matemática, San José, Costa Rica.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1409-24332016000100221</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Una propuesta bioinspirada basada envecindades para particionamiento]]></article-title>
<article-title xml:lang="en"><![CDATA[A bioinspired proposal based onneighborhoods for partitioning]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[BernábeL.]]></surname>
<given-names><![CDATA[Maria Beatriz]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[RodríguezF.]]></surname>
<given-names><![CDATA[Marco Antonio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[GonzálezV.]]></surname>
<given-names><![CDATA[Rogelio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[EstradaA.]]></surname>
<given-names><![CDATA[Martín]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Benemérita Universidad Autónoma de Puebla  Facultad de Ciencias de la Computación]]></institution>
<addr-line><![CDATA[ Puebla]]></addr-line>
<country>MX</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Benemérita Universidad Autónoma de Puebla  Facultad de Ciencias de la Computación]]></institution>
<addr-line><![CDATA[ Puebla]]></addr-line>
<country>MX</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Benemérita Universidad Autónoma de Puebla  Facultad de Ciencias de la Computación]]></institution>
<addr-line><![CDATA[ Puebla]]></addr-line>
<country>MX</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Benemérita Universidad Autónoma de Puebla  Facultad de Ciencias de la Computación]]></institution>
<addr-line><![CDATA[ Puebla]]></addr-line>
<country>MX</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2016</year>
</pub-date>
<volume>23</volume>
<numero>1</numero>
<fpage>221</fpage>
<lpage>239</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.sa.cr/scielo.php?script=sci_arttext&amp;pid=S1409-24332016000100221&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.sa.cr/scielo.php?script=sci_abstract&amp;pid=S1409-24332016000100221&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.sa.cr/scielo.php?script=sci_pdf&amp;pid=S1409-24332016000100221&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[ResumenUna de las principales fuentes de inspiración para proponer nuevos paradigmas computacionales ha sido la observación de la naturaleza. Diversas técnicas en inteligencia artificial han surgido de esta manera.Uno de los esfuerzos que ha causado gran impacto es imitar la manera en que sobreviven otros seres vivos, y en particular, el estudio del funcionamiento cerebral es útil para proponer esquemas análogos y dar solución a algunos problemas. En este punto, los sistemas bioinspirados han surgido como un conjunto de modelos que están basados en el comportamiento y la forma de actuar de ciertos sistemas biológicos, los cuales pueden verse en áreas como la minería de datos e investigación de operaciones donde se distingue el agrupamiento de datos. A partir de la necesidad de resolver problemas de agrupamiento, hemos propuesto un algoritmo de particionamiento bioinspirado de búsqueda por vecindades. Este agrupamiento en una connotación bioinspirada, ha sido planteado después de observar algunas características comunes entre el particionamiento y la conducta del ser humano, donde dichas características pueden ser modeladas. Debido a la alta complejidad del particionamiento hemos incorporado la búsqueda por entorno variable (VNS) en el algoritmo de agrupamiento bioinspirado. La elección de esta metaheurística obedece a la semejanza que hay entre VNS y el modo en que los seres vivos se organizan para resolver situaciones de conflicto.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[AbstractOne of the main sources of inspiration to propose new computational paradigms has been the observation of nature. Diverse artificial intelligence techniques have been created in this way.One of the efforts that has caused great impact is imitating the way some living beings survive, and in particular, the study of the study of brain function is useful to propose analogous schemes and solve some problems. In this point, the bioinspired systems have been originated as a set of models based on the behavior of certain biological systems, which can be seen in areas such as data mining and operations research where data clustering stands out. From the need of solving clustering problems, we have proposed a bioinspired neighborhood search partitioning algorithm. This algorithm, under a bioinspired connotation, has been proposed after observing some of the characteristics in common between clustering and human behavior, where said characteristics can be modeled. Given the high complexity of data clustering, we have incorporated variable neighborhood search (VNS) into the bioinspired clustering algorithm. We chose this metaheuristic because of the similarity that exists between VNS and the way that living beings get organized to solve conflict situations.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[conglomerado geográfico]]></kwd>
<kwd lng="es"><![CDATA[bioinspirado]]></kwd>
<kwd lng="es"><![CDATA[seres vivos]]></kwd>
<kwd lng="es"><![CDATA[búsqueda por vecindades]]></kwd>
<kwd lng="en"><![CDATA[geographical clustering]]></kwd>
<kwd lng="en"><![CDATA[bioinspired]]></kwd>
<kwd lng="en"><![CDATA[living beings]]></kwd>
<kwd lng="en"><![CDATA[neighborhood search]]></kwd>
</kwd-group>
</article-meta>
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