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<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-XLIV-4-W3-2020-295-2020</article-id>
<title-group>
<article-title>GENETIC ALGORITHM FOR OPTIMIZING DISTRIBUTION WITH ROUTE RESTRICTION CONSTRAINT DUE TO TRAFFIC JAMS</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Mouttaki</surname>
<given-names>N.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Benhra</surname>
<given-names>J.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Rguiga</surname>
<given-names>G.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>OSIL Team, Lab LRI, ENSEM, UH2C, Casablanca, Morocco</addr-line>
</aff>
<pub-date pub-type="epub">
<day>23</day>
<month>11</month>
<year>2020</year>
</pub-date>
<volume>XLIV-4/W3-2020</volume>
<fpage>295</fpage>
<lpage>301</lpage>
<permissions>
<copyright-statement>Copyright: © 2020 N. Mouttaki et al.</copyright-statement>
<copyright-year>2020</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLIV-4-W3-2020-295-2020.html">This article is available from https://isprs-archives.copernicus.org/articles/isprs-archives-XLIV-4-W3-2020-295-2020.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLIV-4-W3-2020-295-2020.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/isprs-archives-XLIV-4-W3-2020-295-2020.pdf</self-uri>
<abstract>
<p>&lt;p&gt;The Travelling Salesman Problem (TSP) is a classical problem in combinatorial optimization that consists of finding the shortest tour through all cities such that the salesman visits each city only one time and returns to the starting city. Genetic algorithm is one of the powerful ways to solve problems of traveling salesman problem TSP. The current genetic algorithm aims to take in consideration the constraints happening during the execution of genetic algorithm, such as traffic jams when solving TSP. This program has two important contributions. First one is proposing simple method into taking in consideration an inconvenient route linked to traffic jams. The second one is the use of closeness strategy during the initialization step, which can accelerate the execution time of the algorithm.&lt;/p&gt;&lt;p&gt;The results of the experiments show that the improved algorithm works better than some other algorithms. The conclusion ends the analysis with recommendations and future works.&lt;/p&gt;</p>
</abstract>
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