Digital Twin based Sorting Optimization for Parcel Distribution Centers in Logistics Networks

Digital Twin based Sorting Optimization for Parcel Distribution Centers in Logistics Networks | 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 Digital Twin based Sorting Optimization for Parcel Distribution Centers in Logistics Networks Chuan Huang, Wei Zhang, Ran Li, Yuanming Tian, Renming Liu, Boqun Huang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6932705/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Parcel distribution centers (PDCs) in logistics networks aim to efficiently sort the inbound parcels for downstream destinations via a parcel-sorting system (PSS), by which the parcels are diverted to the assigned grids and packed into bins for outbound truck deliveries. Considering the dynamic parcel movements, random packing behaviors, and conveyor system congestion, maximizing the sorting throughput by assigning grids to parcel destinations presents significant computational challenges. This work establishes the first high fidelity parcel-sorting digital twin system (PSDTS) implemented on an industrial scale that models the real-time interactions among parcels, sorters, and packers, and simulates the throughput performance under a specific sorting plan. Then, to address the computational challenges and operational constraints in PSS, a digital twin-based structured Monte Carlo tree search (DT-SMCTS) framework, combining integer nonlinear programming and geographic destination graph networks, is proposed to optimize the sorting plan. The proposed PSDTS and DT-SMCTS have been widely deployed in 146 PDCs (approximately 30% of all SF Express PDCs in China), and the effectiveness is demonstrated through both the DT numerical results and field experiments: The proposed DT-SMCTS framework increases the average and peak sorting throughputs by 10.56% and 7.72%, respectively, and reduces the number of sorted parcels that require multiple conveyor cycles by 60.81%. Physical sciences/Engineering/Mechanical engineering Scientific community and society/Business and industry/Industry Scientific community and society/Business and industry/Engineering/Mechanical engineering Logistics networks parcel-sorting digital twin (DT) Monte Carlo tree search (MCTS) Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryInformation.pdf Supplementary Information: Practical Parcel Data Analysis, PSDTS Fidelity & Solution Space Derivations 3DVisualizationofPSDTS.mp4 3D Animation of the Parcel-Sorting Digital Twin System Cite Share Download PDF Status: Under Review 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-6932705","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":490389304,"identity":"1e20035f-4014-48b8-85e4-92dc716bfb0a","order_by":0,"name":"Chuan 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