Genetic Algorithm-Based Design and Path Optimization for Robotic Production Lines

Genetic Algorithm-Based Design and Path Optimization for Robotic Production Lines | 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 Genetic Algorithm-Based Design and Path Optimization for Robotic Production Lines ZENGNAN JIN, SHIHUA SUN, RONGCHUANG ZHANG, LINA CHEN This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6583675/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 Amid the global trend toward advanced manufacturing, China has actively enforced energy conservation and carbon reduction policies, imposing stricter requirements on energy consumption and production cycles in robotic assembly lines. Taking the automotive lamp assembly line of a specific enterprise as a case study, this work develops a mathematical model and applies an enhanced genetic algorithm to optimize the mobile trajectories of industrial robots. The optimized system reduces the production cycle by 10% while minimizing energy consumption. This method facilitates the precise configuration of key parameters during the design stage, significantly shortens the commissioning period, and notably improves production efficiency. The proposed approach demonstrates strong practical applicability and broad market potential, underscoring the intelligent and sustainable evolution of future manufacturing systems. Physical sciences/Engineering Physical sciences/Engineering/Mechanical engineering Genetic Algorithm industrial robot Path optimization Production cycle time Mathematical Model 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-6583675","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":464348183,"identity":"99f17355-01aa-422e-8d50-d51d6d306fb3","order_by":0,"name":"ZENGNAN JIN","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAt0lEQVRIiWNgGAWjYFAC5gYDBgYbHn7+BqK1MIK0pMlIzjhAghYgcdjGoCGBSA3yMxIbCn/uOM9jwHCA8cPHHCK0GNxIbDCQPHObx5y5gVly5jZitEgAtRi23eaxbDjAxsxLjBaQwwwS287xGBxIIFILA8hhB9sOkKDF4MzDBsPGtmQeyRkHm4nzi3x78jHDn2129vz8zQc/fCTKYQIJbAYQFjiCiAH8B5gfEKl0FIyCUTAKRioAAP0wN9O1gu1QAAAAAElFTkSuQmCC","orcid":"","institution":"Shenyang Urban Construction University","correspondingAuthor":true,"prefix":"","firstName":"ZENGNAN","middleName":"","lastName":"JIN","suffix":""},{"id":464348184,"identity":"508279b3-512c-4cf6-a76c-1c6ff337ef10","order_by":1,"name":"SHIHUA SUN","email":"","orcid":"","institution":"China Academy of Industrial Internet","correspondingAuthor":false,"prefix":"","firstName":"SHIHUA","middleName":"","lastName":"SUN","suffix":""},{"id":464348185,"identity":"251d284d-a98f-4406-b487-78566fb4a2eb","order_by":2,"name":"RONGCHUANG ZHANG","email":"","orcid":"","institution":"Northeastern University at Qinhuangdao","correspondingAuthor":false,"prefix":"","firstName":"RONGCHUANG","middleName":"","lastName":"ZHANG","suffix":""},{"id":464348186,"identity":"8b9f7a7e-0049-4858-a0ab-f184671ea2ea","order_by":3,"name":"LINA CHEN","email":"","orcid":"","institution":"Shenyang Urban Construction University","correspondingAuthor":false,"prefix":"","firstName":"LINA","middleName":"","lastName":"CHEN","suffix":""}],"badges":[],"createdAt":"2025-05-03 10:53:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6583675/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6583675/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83763429,"identity":"887b4978-2fb4-442f-b066-e79ef7498822","added_by":"auto","created_at":"2025-06-02 10:20:25","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":506759,"visible":true,"origin":"","legend":"","description":"","filename":"scientificreport20250519.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6583675/v1_covered_b9754a9d-38f7-4262-a279-74c284e345c8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genetic Algorithm-Based Design and Path Optimization for Robotic Production Lines","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Genetic Algorithm, industrial robot, Path optimization, Production cycle time, Mathematical Model","lastPublishedDoi":"10.21203/rs.3.rs-6583675/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6583675/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAmid the global trend toward advanced manufacturing, China has actively enforced energy conservation and carbon reduction policies, imposing stricter requirements on energy consumption and production cycles in robotic assembly lines. 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