<?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>0874-5161</journal-id>
<journal-title><![CDATA[Investigação Operacional]]></journal-title>
<abbrev-journal-title><![CDATA[Inv. Op.]]></abbrev-journal-title>
<issn>0874-5161</issn>
<publisher>
<publisher-name><![CDATA[APDIO - Associação Portuguesa de Investigação Operacional]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0874-51612003000200006</article-id>
<title-group>
<article-title xml:lang="pt"><![CDATA[Uma abordagem para o problema da optimização de rotas de veículos baseada em operadores genéticos]]></article-title>
<article-title xml:lang="en"><![CDATA[A Genetic Based Approach to the Vehicle Routing Problem]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Schütz]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pires]]></surname>
<given-names><![CDATA[F. M.]]></given-names>
</name>
<xref ref-type="aff" rid="A02"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,Universidade do Algarve Escola Superior de Tecnologia ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
</aff>
<aff id="A02">
<institution><![CDATA[,Universidade do Algarve Faculdade de Ciências e Tecnologia ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2003</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2003</year>
</pub-date>
<volume>23</volume>
<numero>2</numero>
<fpage>197</fpage>
<lpage>209</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_arttext&amp;pid=S0874-51612003000200006&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_abstract&amp;pid=S0874-51612003000200006&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_pdf&amp;pid=S0874-51612003000200006&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[In its basic form the vehicle routing problem (VRP) consists of serving a set of clients with known locations and demands by a fixed fleet of vehicles of limited capacity, minimizing the total route length. All vehicles are located at a common depot with known location. This is a NP-hard problem. The few methods developed to solve the problem exactly are very time consuming and they are only feasible for small dimension problems. So, the most efficient approaches are based on heuristic algorithms. More recently some meta-heuristics, mainly based on Tabu search, have been developed to the VRP. In this work we present a Genetic algorithm to the basic version of the VRP. We describe the way we have adjusted the genetic operators to the problem. We report and analyse the results of a computational study with a set of known test problems.]]></p></abstract>
<abstract abstract-type="short" xml:lang="pt"><p><![CDATA[A versão básica do Problema da Optimização de Rotas de Veículos consiste em determinar um conjunto de rotas a efectuar por uma frota de veículos, estacionada num depósito central, para servir um conjunto fixo de clientes, minimizando a distância total percorrida. O número de veículos e respectivas capacidades, as localizações e procuras dos clientes, bem como a localização do depósito são conhecidas. Este problema pertence à classe dos problemas NP-difíceis. Os poucos métodos exactos que foram desenvolvidos para o resolver são demasiado demorados e apenas exequíveis para a generalidade dos problemas de pequena dimensão (até cerca de 50 clientes). Assim, as abordagens mais comuns e eficientes baseiam-se em métodos heurísticos. Mais recentemente várias meta-heurísticas, principalmente baseadas em Pesquisa Tabu, têm sido desenvolvidas para o Problema da Optimização de Rotas de Veículos. Neste trabalho expõe-se um Algoritmo Genético para a versão básica do Problema de Optimização de Rotas de Veículos. Apresenta-se a forma como se adaptaram os operadores genéticos a este problema. Descreve-se o estudo computacional realizado, com um conjunto de problemas-teste conhecidos da literatura, e analisam-se os resultados obtidos.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Vehicle Routing Problem]]></kwd>
<kwd lng="en"><![CDATA[Heuristics]]></kwd>
<kwd lng="en"><![CDATA[Genetic Algorithms]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[ <p ALIGN="CENTER"><B>Uma abordagem para o problema da optimiza&#231;&#227;o de    rotas de ve&#237;culos baseada em operadores gen&#233;ticos</B></p>     <p ALIGN="CENTER">G. Sch&#252;tz *</p>       <P ALIGN="CENTER">F. M. Pires †</P>      <P ALIGN="CENTER">* Escola Superior de Tecnologia - Universidade do Algarve  </p>        <P ALIGN="CENTER">† Faculdade de Ci&#234;ncias e Tecnologia - Universidade do Algarve </p>     <P ALIGN="CENTER"><a href="mailto:mpires@ualg.pt">mpires@ualg.pt</a></p>     <P ALIGN="CENTER">&nbsp;</p>     <P ALIGN="CENTER">&nbsp;</p>        <p align="center"> <b>Title:</b> A Genetic Based Approach to the Vehicle Routing    Problem</p>     <p align="center"><b>Abstract</b></p>       ]]></body>
<body><![CDATA[<P align="justify"> In its basic form the vehicle routing problem (VRP) consists    of serving a set of clients with known locations and demands by a fixed fleet    of vehicles of limited capacity, minimizing the total route length. All vehicles    are located at a common depot with known location.</p>     <P align="justify"> This is a NP-hard problem. The few methods developed to solve    the problem exactly are very time consuming and they are only feasible for small    dimension problems. So, the most efficient approaches are based on heuristic    algorithms. More recently some meta-heuristics, mainly based on Tabu search,    have been developed to the VRP.</p>     <P align="justify"> In this work we present a Genetic algorithm to the basic version    of the VRP. We describe the way we have adjusted the genetic operators to the    problem. We report and analyse the results of a computational study with a set    of known test problems.</p>     <P align="justify"> <b>Keywords:</b> Vehicle Routing Problem, Heuristics, Genetic    Algorithms</p>     <P align="justify">&nbsp;</p>     <P>&nbsp;</p>        <p align="center"><b>Resumo</b></p>       <P align="justify"> A vers&#227;o b&#225;sica do Problema da Optimiza&#231;&#227;o    de Rotas de Ve&#237;culos consiste em determinar um conjunto de rotas a efectuar    por uma frota de ve&#237;culos, estacionada num dep&#243;sito central, para    servir um conjunto fixo de clientes, minimizando a dist&#226;ncia total percorrida.    O n&#250;mero de ve&#237;culos e respectivas capacidades, as localiza&#231;&#245;es    e procuras dos clientes, bem como a localiza&#231;&#227;o do dep&#243;sito s&#227;o    conhecidas.</p>     <P align="justify"> Este problema pertence &#224; classe dos problemas NP-dif&#237;ceis.    Os poucos m&#233;todos exactos que foram desenvolvidos para o resolver s&#227;o    demasiado demorados e apenas exequ&#237;veis para a generalidade dos problemas    de pequena dimens&#227;o (at&#233; cerca de 50 clientes). Assim, as abordagens    mais comuns e eficientes baseiam-se em m&#233;todos heur&#237;sticos. Mais recentemente    v&#225;rias meta-heur&#237;sticas, principalmente baseadas em Pesquisa Tabu,    t&#234;m sido desenvolvidas para o Problema da Optimiza&#231;&#227;o de Rotas    de Ve&#237;culos.</p>     <P align="justify"> Neste trabalho exp&#245;e-se um Algoritmo Gen&#233;tico para    a vers&#227;o b&#225;sica do Problema de Optimiza&#231;&#227;o de Rotas de Ve&#237;culos.    Apresenta-se a forma como se adaptaram os operadores gen&#233;ticos a este problema.    Descreve-se o estudo computacional realizado, com um conjunto de problemas-teste    conhecidos da literatura, e analisam-se os resultados obtidos.</p>     ]]></body>
<body><![CDATA[<P>&nbsp;</p>        <P>Texto completo disponível apenas em PDF.</p>      <P>Full text only available in PDF format.</p>     <P>&nbsp;</p>       <P>&nbsp;</p>         <p> <b> Bibliografia</b> </p>       <!-- ref --><p>1. BULLNHEIMER, B.; R. F. HARTL; C. STRAUSS, Applying the ant system to the    vehicle routing problem, in Metaheuristics: Advances and Trends in Local Search    for Optimization, editado por S. Voss, S. Martello, I. Osman, C. Roucairol,    Kluwer Academic Publishers (1999). &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=326695&pid=S0874-5161200300020000600001&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p>2. CHRISTOFIDES, N.; A. MINGOZZI; P. TOTH, The vehicle routing problem, in    Combinatorial Optimization, editado por N. Christofides, A. Mingozzi, P. Toth    e C. 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