<?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>S2007-07052017000100257</article-id>
<article-id pub-id-type="doi">10.21640/ns.v9i18.840</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Numerical analysis of minimum cost network flow with queuing stations: the M/M/1 case]]></article-title>
<article-title xml:lang="es"><![CDATA[Análisis numérico de flujo a costo mínimo en redes con estaciones de espera: el caso M/M/1]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández-González]]></surname>
<given-names><![CDATA[Salvador]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Flores de la Mota]]></surname>
<given-names><![CDATA[Idalia]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Jiménez-García]]></surname>
<given-names><![CDATA[José Alfredo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández-Ripalda]]></surname>
<given-names><![CDATA[Manuel Darío]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Instituto Tecnológico de Celaya Departamento de Ingeniería Industrial ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Nacional Autónoma de México Facultad de Ingeniería ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2017</year>
</pub-date>
<volume>9</volume>
<numero>18</numero>
<fpage>257</fpage>
<lpage>289</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2007-07052017000100257&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2007-07052017000100257&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2007-07052017000100257&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract In a network the nodes represent stations, warehouses, distribution centers and customers and not just materials but also information circulate, so the minimum cost flow model, that only takes transport costs into account is one of the tools used to support the decision-making. In reality, the nodes provide a service which requires a service time, the servicing follows a discipline and also a queue is formed, generating the respective service and queuing costs. A modified version of the minimum cost flow model is proposed in this paper for the optimization of the flow in a queuing network. A variety of cases were solved. An acceptable level of accuracy was observed in the calculation of the time cycle and work in progress. The results indicate that the optimum solution tends to balance the workload along the network. This paper is of interest to administrators and people in charge of supply chains and is useful for decision-making in the medium or long time.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En una red los nodos representan estaciones, almacenes, centros de distribución y clientes y circulan tanto materiales como información, por lo que una herramienta utilizada para apoyar la toma de decisiones es el modelo de flujo a costo mínimo que toma en cuenta únicamente costos de transporte. En la realidad los nodos prestan un servicio el cual requiere un tiempo de servicio, la atención sigue una disciplina y además se forma una fila de espera. En este trabajo se propone una modificación del modelo de flujo a costo mínimo para la optimización en redes de líneas de espera. Se resolvieron varios casos donde se observa un grado de exactitud aceptable en el cálculo del tiempo de ciclo y trabajo en proceso. El trabajo es de interés para los administradores y/o responsables de las cadenas de abasto y útil para la toma de decisiones a mediano y largo plazo.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[network flow]]></kwd>
<kwd lng="en"><![CDATA[supply chain]]></kwd>
<kwd lng="en"><![CDATA[queueing networks]]></kwd>
<kwd lng="en"><![CDATA[cycle time]]></kwd>
<kwd lng="en"><![CDATA[work in process]]></kwd>
<kwd lng="es"><![CDATA[flujo en redes]]></kwd>
<kwd lng="es"><![CDATA[cadena de abasto]]></kwd>
<kwd lng="es"><![CDATA[redes de colas]]></kwd>
<kwd lng="es"><![CDATA[tiempo de ciclo]]></kwd>
<kwd lng="es"><![CDATA[trabajo en proceso]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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