Two-Stage Genetic Algorhitm for Optimization Logistics Network for Groupage Delivery

Two-Stage Genetic Algorhitm for Optimization Logistics Network for Groupage Delivery | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Two-Stage Genetic Algorhitm for Optimization Logistics Network for Groupage Delivery Ivan P. Malashin, Vadim S. Tynchenko, Igor S. Masich, Denis A. Sukhanov, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4450313/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study explores groupage delivery optimization through a two-stage GA framework. The goal of optimization is to define locations of regional branch warehouses of Logistics Network to reduce transportation costs. The first stage of the GA focuses on identifying branch warehouses from a list of cities and uses the standard binary string approach, while the second stage solves Vehicle Routing Problem (VRP) using combinatorial GA. This research contributes to advancing logistics optimization methodologies and provides valuable insights for solving Location Routing Problem (LRP) which entails two problems: the Facility Location Problem (FLP) and the Multiple Vehicle Routing Problem (MVRP). Physical sciences/Mathematics and computing/Computational science Physical sciences/Mathematics and computing/Software Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4450313","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":309996332,"identity":"894cb5d1-466f-4b93-b92b-53e0a3763b06","order_by":0,"name":"Ivan P. 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