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        <journal-meta>
            <journal-title-group>
                <journal-title>Journal of Global Humanities and Social Sciences</journal-title>
            </journal-title-group>
            <issn media_type="print">2737-5374</issn>
            <issn media_type="electronic">2737-5382</issn>
            <publisher>
                <publisher-name>BONI FUTURE DIGITAL PUBLISHING CO.,LIMITED </publisher-name>
            </publisher>
            <url>https://ojs.bonfuturepress.com/index.php/GHSS/article/view/1739</url>
            <volume>6</volume>
            <issue>1</issue>
            <year>2025</year>
            <published-time>2025-01-24</published-time>
            <title>Overview Discourse on Inherent Distinction of Multiobjective Optimization in Routing   Heuristics for Multi-Depot Vehicle Instances</title>
            <author>Shir Li Wang,Farid Morsidi,Haldi Budiman,Theam Foo Ng</author>
            <abstract>This paper reviews the research methodologies used in earlier years on the benefits and traits reflected by multi-depot vehicle routing  problem  (MDVRP)  instances  and  assesses  the  efficacy  of various  improvised  techniques  to  improve  the  current  recurrent problems in routing procedures. Management of logistics involves moving finished goods from depots to end-user clients. Routing and scheduling systems that are improved will be able to serve a more significant number of customers in a shorter amount of time while also  increasing  customer  satisfaction.  To  thoroughly  discuss  the   current   state  of  MDVRP  implementation  in  routing  heuristics, an  analysis  of  the   selected  approaches  involving  multi-depot  task  distribution  under  VRP  incorporations  is  further  extrapolated. These approaches address the most common routing issues involving constraints like cost optimality, time window impositions, and load capacity  flexibility.  Recent  research  focuses  on  the  advantages,  proficiency,  problem  magnitude,  and  adaptability  in  MDVRP. The MDVRP framework can still be significantly improved by reducing routing costs with efficient heuristics to generate optimized solutions.</abstract>
            <keywords>vehicle routing problem,multi-depot VRP,routing heuristics,scheduling routing,logistics problem</keywords>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.61360/BoniGHSS252017390102</article-id>
        </article-meta>
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