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<journal-meta>
<journal-id journal-id-type="publisher">global-journal-of-computer-science-and-technology-d-neural-ai</journal-id>
<journal-title-group>
<journal-title>Global Journal of Computer Science and Technology - D: Neural &amp; AI</journal-title>
</journal-title-group>
<issn publication-format="print">0975-4350</issn>
<issn publication-format="electronic">0975-4172</issn>
<publisher><publisher-name>Global Journals Publishing Group Incorporated</publisher-name></publisher>
<self-uri xlink:href="https://globaljournals.org/journal-seo-export/jats/83763.xml" />
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<article-id pub-id-type="publisher-id">83763</article-id>
<title-group>
<article-title>Vehicle Routing Optimization with Ant Colony Optimization Algorithm Integrated with Map Analyzer API</article-title>
<subtitle>ACO Algorithm for Optimal Vehicle Routing</subtitle>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Tanzim</surname><given-names>Mashrure</given-names></name><xref ref-type="aff" rid="aff1" />
</contrib>
</contrib-group>
<aff id="aff1">BANGLADESH, Bangladesh University of Professionals</aff>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2025-01-07">
<day>07</day>
<month>01</month>
<year>2025</year>
</pub-date>
<volume>24</volume>
<issue>D2</issue>
<fpage>55</fpage>
<lpage>61</lpage>
<abstract><p>Ant colony optimization (ACO) algorithm can be used to solve combinatorial optimization problems such as the traveling salesman problem. In this work, an endeavor has been taken in finding the proper algorithm which could be used for routing problems in different real-life situations. Taking into due cognizance of the limitations of the existing routing system, the outcome of this work will facilitate a more convenient way of finding destinations for the users in term of accuracy and time over the existing routing systems. The cost of the program will also be lesser than contemporary systems. To accomplish this, a system has been built that can take a map image with source and destinations denoted; and find an optimal path for them. The work has been concluded with suggestions to future researchers who might look to build a system that can solve any type of routing problems using TSP.</p></abstract>
<kwd-group kwd-group-type="author-generated">
<kwd>swarm intelligence</kwd>
<kwd>vehicle routing</kwd>
<kwd>ant colony optimization.</kwd>
</kwd-group>
<self-uri content-type="pdf" xlink:href="https://globaljournals.org/GJCST_Volume24/6-Vehicle-Routing.pdf" />
<self-uri content-type="html" xlink:href="https://globaljournals.org/scholarly-articles/vehicle-routing-optimization-with-ant-colony-optimization-algorithm-integrated-with-map-analyzer-api/" />
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<title>Full Text</title>
<p>Ant colony optimization (ACO) algorithm can be used to solve combinatorial optimization problems such as the traveling salesman problem. In this work, an endeavor has been taken in finding the proper algorithm which could be used for routing problems in different real-life situations. Taking into due cognizance of the limitations of the existing routing system, the outcome of this work will facilitate a more convenient way of finding destinations for the users in term of accuracy and time over the existing routing systems. The cost of the program will also be lesser than contemporary systems. To accomplish this, a system has been built that can take a map image with source and destinations denoted; and find an optimal path for them. The work has been concluded with suggestions to future researchers who might look to build a system that can solve any type of routing problems using TSP.</p>
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