<?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>2007-0705</journal-id>
<journal-title><![CDATA[Nova scientia]]></journal-title>
<abbrev-journal-title><![CDATA[Nova scientia]]></abbrev-journal-title>
<issn>2007-0705</issn>
<publisher>
<publisher-name><![CDATA[Universidad de La Salle Bajío A. C., Coordinación de Investigación]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2007-07052015000300081</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Mejorando la planificación de sistemas territoriales con optimización metaheurística]]></article-title>
<article-title xml:lang="en"><![CDATA[Improving territory design planning through metaheuristic optimization]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ríos Mercado]]></surname>
<given-names><![CDATA[Roger Z.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma de Nuevo León Facultad de Ingeniería Mecánica y Eléctrica Posgrado en Ingeniería de Sistemas]]></institution>
<addr-line><![CDATA[San Nicolás de los Garza NL]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2015</year>
</pub-date>
<volume>7</volume>
<numero>15</numero>
<fpage>81</fpage>
<lpage>95</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2007-07052015000300081&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2007-07052015000300081&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2007-07052015000300081&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Introducción:  Este artículo tiene por objetivo ilustrar cómo la ciencia puede impactar positivamente en procesos de decisiones de carácter industrial. El problema consiste en encontrar una partición del conjunto total de unidades geográficas (bloques) que minimice una única función de dispersión territorial. Esta medida de desempeño es equivalente a maximizar la compacidad de los territorios, es decir, obtener diseños donde ls unidades geográficas estén lo más cercanas entre sí. La solución debe satisfacer además otros requerimientos como equilibrar las distintas medidas de actividad entre los distintos territorios, así como contigüidad de territorios. Como resultado se tiene un modelo mono-objetivo de optimización combinatoria.  Método:  Para tal efecto, se presenta un método metaheurístico de solución, denominado GRASP, para la resolución de un problema de diseño de territorios comerciales, motivado por una aplicación real de una compañía de distribución de bebidas embotelladas. El método integra componentes de construcción de soluciones y de búsqueda local o mejora de las mismas que intentan explotar inteligentemente la estructura matemática del problema.  Resultados:  El algoritmo se ha evaluado en varios conjuntos de instancias generados aleatoriamente a partir de datos reales proporcionados por el socio industrial. Los resultados obtenidos indican la eficacia del método propuesto dado que, en tiempos de cómputo relativamente rápidos, pudieron obtenerse soluciones de calidad muy superior a la de las obtenidas por la empresa, tanto respecto a la medida de compacidad, como respecto a la satisfacción de todas las restricciones. Previo a abordar el trabajo, la empresa no podía encontrar solcuiones que satisfacieran grados de balence, por ejemplo, inferiores al 20%. EL método propuesto encuentra siempre soluciones factibles con desbalances menores al 5%.  Conclusión:  Se ha ilustrado cómo los problemas de toma de decisiones industriales pueden ser apoyados mediante modelos y técnicas de Investigación de Operaciones, resultando en planes territoriales de mejor calidad.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Introduction:  The goal of this paper is to illustrate how science can aid and have a positive impact on industrial decision-making problems. The combinatorial optimization problem consists of finding a partition of the set of basic units into territories so as to maximize a unique compactness objective function. The solution must also satisfy several constraints or requirements such as, balancing the different node activity measures among territories and territory contiguity.  Method:  We present a metaheuristic solution method, called GRASP, to a commercial territory design problem motivated by a real-world application in a beverage distribution firm. The heuristic integrates both construction and local search methods that attempt to intelligently exploit the mathematical structure of the problem.  Results:  The algorithm has been tested in several data sets. The results show the effectiveness of the proposed approach. GRASP obtained solutions of much better quality (in terms of both its dispersion measure and its feasibility with respect to the balancing constraints) than those found by the firm method in relatively fast computation times. Previous to this work, the company was struggling in obtaining design plans with less than 20% imbalance. The proposed method can always obtain design plans with less than 5% imbalance  Conclusion:  It has been illustrated how Operations Research models and techniques can aid decision-making problems, resulting in territory plans of better quality.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Investigación de operaciones]]></kwd>
<kwd lng="es"><![CDATA[optimización combinatoria]]></kwd>
<kwd lng="es"><![CDATA[diseño territorial]]></kwd>
<kwd lng="es"><![CDATA[metaheurísticas]]></kwd>
<kwd lng="es"><![CDATA[GRASP]]></kwd>
<kwd lng="en"><![CDATA[Operations research]]></kwd>
<kwd lng="en"><![CDATA[combinatorial optimization]]></kwd>
<kwd lng="en"><![CDATA[territory design]]></kwd>
<kwd lng="en"><![CDATA[metaheuristics]]></kwd>
<kwd lng="en"><![CDATA[GRASP]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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