<?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>2218-3620</journal-id>
<journal-title><![CDATA[Revista Universidad y Sociedad]]></journal-title>
<abbrev-journal-title><![CDATA[Universidad y Sociedad]]></abbrev-journal-title>
<issn>2218-3620</issn>
<publisher>
<publisher-name><![CDATA[Editorial "Universo Sur"]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2218-36202023000300232</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Non-dominated sorting genetic algorithm-ii arrangements for optimal electrical distribution networks reconfiguration]]></article-title>
<article-title xml:lang="es"><![CDATA[Arreglos al algoritmo genético de clasificación no dominada-ii para la reconfiguración óptima de redes de distribución eléctrica]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Crespo Sánchez]]></surname>
<given-names><![CDATA[Gustavo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Abril]]></surname>
<given-names><![CDATA[Ignacio Pérez]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Cienfuegos &#8220;Carlos Rafael Rodríguez&#8221;  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Central &#8220;Marta Abreu&#8221; de Las Villas  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Cuba</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2023</year>
</pub-date>
<volume>15</volume>
<numero>3</numero>
<fpage>232</fpage>
<lpage>241</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S2218-36202023000300232&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S2218-36202023000300232&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S2218-36202023000300232&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT Radiality constraint typically increases genetic algorithms complexity considering that distribution network reconfiguration is - by nature - non-differentiable, mixed integer and highly complex combinatorial. Genetic Algorithms&#8217; potentialities can be seized when coding is enough efficient. Paper presents non-dominated sorting genetic algorithm-II arrangements, implemented in MatLab to solve optimal electrical distribution networks reconfiguration. Initial population is created randomly by using a heuristic approach and genetic operators for generating feasible individuals in every genetic evolution stage which besides are adapted with graph theory help for transforming initial population's infeasible individuals that not satisfied radiality constraint, as well as for avoiding new infeasible individual&#8217;s generation and thus, sidestepping the boring mesh check and reducing search space and computational burden. Unlike previous authors that employed an integer-composed chromosome that directly selects a single branch to open from each fundamental loop vector as well as modified genetic operators, the algorithm&#8217;s arrangements and a new coding used that ensures chromosome viability for all gene values has been the employed approach. That way, crossover and mutation do not need special genetic operators. Proposal efficacy has been tested with 33-bus and 70-bus test systems and results are promising and better than precedent proposals.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN La restricción de configuración radial generalmente aumenta la complejidad de los algoritmos genéticos considerando que la reconfiguración de redes de distribución es, por naturaleza, no diferenciable, entera mixta y combinatoria altamente compleja. Las potencialidades de los algoritmos genéticos se pueden aprovechar cuando la codificación es lo suficientemente eficiente. El artículo presenta arreglos del algoritmo genético de clasificación no dominada-II implementado en MatLab para resolver la reconfiguración óptima de redes de distribución eléctrica. La población inicial se crea aleatoriamente mediante el uso de un enfoque heurístico y operadores genéticos para generar individuos factibles en cada etapa de evolución genética que, además, se adaptan con la ayuda de la teoría de grafos para transformar los individuos no factibles de la población inicial que no cumplieron con la restricción de configuración radial, así como para evitar la generación de nuevos individuos no factibles y por lo tanto, eludiendo el tedioso chequeo de la malla y reduciendo el espacio de búsqueda y la carga computacional. A diferencia de autores anteriores que emplearon un cromosoma compuesto por números enteros que selecciona directamente una sola rama para abrir en cada vector de lazo fundamental, así como operadores genéticos modificados, el enfoque empleado utiliza los arreglos realizados al algoritmo y una nueva codificación que garantizan la viabilidad cromosómica para todos los valores genéticos. De esa forma, el cruzamiento y la mutación no necesitan operadores genéticos especiales. La eficacia de la propuesta se probó con sistemas de prueba de 33 y 70 barras y los resultados son prometedores y mejores que las propuestas precedentes.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Distribution systems]]></kwd>
<kwd lng="en"><![CDATA[Genetic algorithms]]></kwd>
<kwd lng="en"><![CDATA[Network reconfiguration]]></kwd>
<kwd lng="en"><![CDATA[NSGA-II arrangements]]></kwd>
<kwd lng="en"><![CDATA[optimization problem]]></kwd>
<kwd lng="es"><![CDATA[Algoritmos genéticos]]></kwd>
<kwd lng="es"><![CDATA[Arreglos al NSGA-II]]></kwd>
<kwd lng="es"><![CDATA[Problemas de optimización reconfiguración de redes]]></kwd>
<kwd lng="es"><![CDATA[Sistemas de distribución]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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