Inverse Scheduling Method for Aircraft Flat-tail Assembly Production Based on Improved Genetic Algorithm

Inverse Scheduling Method for Aircraft Flat-tail Assembly Production Based on Improved Genetic Algorithm | 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 Inverse Scheduling Method for Aircraft Flat-tail Assembly Production Based on Improved Genetic Algorithm Tengda Li, Min Hua, Junliang Wang, Wei Qin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7336541/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract The manufacturing process of the aircraft flat-tail assembly is complex and discrete. It typically involves manual assembly at fixed stations with variable shift teams. However, uncertainties can arise even after a scheduling scheme is created, leading to non-optimal or even infeasible schedules. To address this issue, a new scheduling strategy called ‘inverse scheduling’ has been proposed by incorporating the concept of inverse optimization. Notably, this is the first application of inverse scheduling in the complex manufacturing process of aircraft flat-tail assembly. This paper presents a multi-objective optimization model for the inverse scheduling problem of flat-tail assembly production. The scheduling objectives include minimizing the maximum delay penalty cost and minimizing the assembly time adjustment cost. To address the limitations of traditional mathematical planning methods in terms of efficiency and solution quality, an improved genetic algorithm is proposed. This algorithm combines the genetic algorithm with a local search strategy to solve the large-scale inverse scheduling problem. Additionally, an inverse scheduling strategy based on the self-adaptive tolerance-driving mechanism is designed to enhance the algorithm's efficiency and effectively handle order delay exception events. The effectiveness of the self-adaptive tolerance driving mechanism and the inverse scheduling method is verified through case studies in enterprises. Physical sciences/Engineering Physical sciences/Mathematics and computing Flat-tail assembly production Self-adaptive driving mechanism Inverse scheduling Improved genetic algorithm Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 17 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 11 Sep, 2025 Reviews received at journal 09 Sep, 2025 Reviews received at journal 07 Sep, 2025 Reviews received at journal 06 Sep, 2025 Reviewers agreed at journal 03 Sep, 2025 Reviewers agreed at journal 31 Aug, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers invited by journal 28 Aug, 2025 Editor invited by journal 19 Aug, 2025 Editor assigned by journal 14 Aug, 2025 Submission checks completed at journal 13 Aug, 2025 First submitted to journal 09 Aug, 2025 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. 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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-7336541","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":509968561,"identity":"2b3f6730-f31b-4b29-9a92-4af23e1e4f4f","order_by":0,"name":"Tengda Li","email":"","orcid":"","institution":"Shanghai Jiao Tong University, USC-SJTU Institute of Cultural and Creative Industry","correspondingAuthor":false,"prefix":"","firstName":"Tengda","middleName":"","lastName":"Li","suffix":""},{"id":509968564,"identity":"5b3eb3a1-41de-4610-9a10-f0ae3b624800","order_by":1,"name":"Min Hua","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYBACAxCRwGDDwNgAYrERryWNgbGNJC0MDIehqonRYi6R/HTDwx3n7Znn9xgwfCg7zMA/uwG/FssZaWY3Es/cTmxs4zFgnHHuMIPEnQMEHHYjAail7XYCI1ALM2/bYQYDiQRCWtK/AbWcswdr+UuclhyQLQcYQQ5jZiRKy5k3ZUAtyUC/pBUc7DmXziNxg5CW4+nbbv5ss7M3bD688cGPMms5/hkEtMCBYQMDwwEgzUOkeiCQJ17pKBgFo2AUjDQAACnRRd7h9J1dAAAAAElFTkSuQmCC","orcid":"","institution":"Shanghai Jiao Tong University, USC-SJTU Institute of Cultural and Creative Industry","correspondingAuthor":true,"prefix":"","firstName":"Min","middleName":"","lastName":"Hua","suffix":""},{"id":509968570,"identity":"9ab6655c-7040-4cdc-ac31-61ccd9ca1b12","order_by":2,"name":"Junliang Wang","email":"","orcid":"","institution":"Donghua University","correspondingAuthor":false,"prefix":"","firstName":"Junliang","middleName":"","lastName":"Wang","suffix":""},{"id":509968573,"identity":"248e36de-dccd-4c92-9d7b-435e4d32a082","order_by":3,"name":"Wei Qin","email":"","orcid":"","institution":"Shanghai Jiao Tong University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Qin","suffix":""}],"badges":[],"createdAt":"2025-08-10 03:23:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7336541/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7336541/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-23898-9","type":"published","date":"2025-11-17T15:57:48+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":96650120,"identity":"fc4c0155-08ba-4f8c-bfce-1d509959cad0","added_by":"auto","created_at":"2025-11-24 16:08:16","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":514550,"visible":true,"origin":"","legend":"","description":"","filename":"ScientificReportsInverseSchedulingMethodforAircraftFlattailAssemblyProductionBasedonImprovedGeneticAlgorithm.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7336541/v1_covered_61ae0ee5-8719-4d1a-a703-26942a8917f4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Inverse Scheduling Method for Aircraft Flat-tail Assembly Production Based on Improved Genetic Algorithm","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Flat-tail assembly production, Self-adaptive driving mechanism, Inverse scheduling, Improved genetic algorithm","lastPublishedDoi":"10.21203/rs.3.rs-7336541/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7336541/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe manufacturing process of the aircraft flat-tail assembly is complex and discrete. It typically involves manual assembly at fixed stations with variable shift teams. However, uncertainties can arise even after a scheduling scheme is created, leading to non-optimal or even infeasible schedules. To address this issue, a new scheduling strategy called \u0026lsquo;inverse scheduling\u0026rsquo; has been proposed by incorporating the concept of inverse optimization. Notably, this is the first application of inverse scheduling in the complex manufacturing process of aircraft flat-tail assembly. This paper presents a multi-objective optimization model for the inverse scheduling problem of flat-tail assembly production. The scheduling objectives include minimizing the maximum delay penalty cost and minimizing the assembly time adjustment cost. To address the limitations of traditional mathematical planning methods in terms of efficiency and solution quality, an improved genetic algorithm is proposed. 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