Research on two-stage optimization model of Electric Towing Vehicles at Airports

Research on two-stage optimization model of Electric Towing Vehicles at Airports | 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 Research Article Research on two-stage optimization model of Electric Towing Vehicles at Airports Yanxi Liu, Cong Dou, Dandan Zhang, Jie Ouyang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7370197/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 introduces an innovative two-stage optimization model for Electric Towing Vehicle (ETV) scheduling at airports, aiming to resolve the conflict between resource investment and operational efficiency. Given that aircraft ground taxiing contributes significantly to aviation carbon emissions, with about 7% of total flight fuel consumed during this phase, ETVs emerge as a key solution for the industry’s low-carbon transition.The first stage of the model minimizes the number of ETVs, setting a baseline for resource input. The second stage focuses on optimizing task allocation, with two schemes: one prioritizing minimum scheduling time and the other aiming for optimal task allocation equilibrium. The model addresses gaps in existing studies by integrating flight imbalance simulation (using the Cellular Automaton-CA model) and dynamic hub allocation, which were previously overlooked. The Genetic Greedy Hybrid Algorithm (GGHA) is applied to ensure global optimality and efficient task allocation , with CA simulating real-world airport operations to determine flight service windows for model input.A case study at Tianjin Binhai International Airport validates the model’s effectiveness. The proposed method reduces ETV requirements by approximately 19.4% compared to the current scheme. It offers two distinct schemes for comparison within the second stage: the minimum scheduling time scheme shortens total scheduling time by about 1.1%, while the optimal task allocation equilibrium scheme reduces task load variance by 82%, enhancing resource utilization and long-term system stability. This research provides a practical framework for airports to enhance ETV scheduling efficiency and achieve sustainable development. Electric Towing Vehicles quantity two-stage optimization Cellular Automata model airport ground support operations Genetic Greedy Hybrid Algorithm Full Text Additional Declarations No competing interests reported. Supplementary Files ResearchontwostageoptimizationmodelofElectricTowingVehiclesatAirports.zip 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-7370197","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":500631744,"identity":"9d932f34-90db-49b2-98f5-0f5f23d25d9e","order_by":0,"name":"Yanxi Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIie3PoQ7CMBCA4WtIUIPZYVYeodMQnuXIkmHQ01NTJNgmPAVvUFIxsxTbBMRm0JMzJLQJAkU3R0J/dZfcJw7A5/vNiEBYv+fpQGNINpYAyBGEaQTRllca8rSBLpcQngoHqQWIbXlLuM4Y4UpCdBcOUh07SxD0HiazUgKL0EHMF4YopJY8B5GqsEQgs4QMIQv7C6o0OdcPdjmoXRBpB5lrJG2fb2hcpW3T56s45A6yFB+LnYPv9yZaOE98Pp/v73sBknJHk0C+FGMAAAAASUVORK5CYII=","orcid":"","institution":"Civil Aviation University of China","correspondingAuthor":true,"prefix":"","firstName":"Yanxi","middleName":"","lastName":"Liu","suffix":""},{"id":500631746,"identity":"859b4596-68cd-4d97-ae48-dadcc273cd17","order_by":1,"name":"Cong Dou","email":"","orcid":"","institution":"Civil Aviation University of China","correspondingAuthor":false,"prefix":"","firstName":"Cong","middleName":"","lastName":"Dou","suffix":""},{"id":500631747,"identity":"f40b4b3c-5dc3-4619-84bf-3c7632e374c1","order_by":2,"name":"Dandan Zhang","email":"","orcid":"","institution":"Civil Aviation University of China","correspondingAuthor":false,"prefix":"","firstName":"Dandan","middleName":"","lastName":"Zhang","suffix":""},{"id":500631750,"identity":"8cd69749-b90e-4e44-9baf-af206a382446","order_by":3,"name":"Jie Ouyang","email":"","orcid":"","institution":"Civil Aviation University of China","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Ouyang","suffix":""}],"badges":[],"createdAt":"2025-08-14 06:08:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7370197/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7370197/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":94473296,"identity":"dd069212-ad16-47a1-a35a-98ab52c17e5d","added_by":"auto","created_at":"2025-10-27 15:43:48","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3299102,"visible":true,"origin":"","legend":"","description":"","filename":"ResearchontwostageoptimizationmodelofElectricTowingVehiclesatAirports.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7370197/v1_covered_b968ab48-8873-46be-90aa-097ae719c113.pdf"},{"id":89448563,"identity":"3a8ce074-2180-4616-9119-9c9ab76f39ba","added_by":"auto","created_at":"2025-08-20 05:47:38","extension":"zip","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2583497,"visible":true,"origin":"","legend":"","description":"","filename":"ResearchontwostageoptimizationmodelofElectricTowingVehiclesatAirports.zip","url":"https://assets-eu.researchsquare.com/files/rs-7370197/v1/a8c35d660cc342a885421d58.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research on two-stage optimization model of Electric Towing Vehicles at Airports","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Electric Towing Vehicles quantity, two-stage optimization, Cellular Automata model, airport ground support operations, Genetic Greedy Hybrid Algorithm","lastPublishedDoi":"10.21203/rs.3.rs-7370197/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7370197/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This study introduces an innovative two-stage optimization model for Electric Towing Vehicle (ETV) scheduling at airports, aiming to resolve the conflict between resource investment and operational efficiency. Given that aircraft ground taxiing contributes significantly to aviation carbon emissions, with about 7% of total flight fuel consumed during this phase, ETVs emerge as a key solution for the industry’s low-carbon transition.The first stage of the model minimizes the number of ETVs, setting a baseline for resource input. The second stage focuses on optimizing task allocation, with two schemes: one prioritizing minimum scheduling time and the other aiming for optimal task allocation equilibrium. The model addresses gaps in existing studies by integrating flight imbalance simulation (using the Cellular Automaton-CA model) and dynamic hub allocation, which were previously overlooked. The Genetic Greedy Hybrid Algorithm (GGHA) is applied to ensure global optimality and efficient task allocation , with CA simulating real-world airport operations to determine flight service windows for model input.A case study at Tianjin Binhai International Airport validates the model’s effectiveness. The proposed method reduces ETV requirements by approximately 19.4% compared to the current scheme. It offers two distinct schemes for comparison within the second stage: the minimum scheduling time scheme shortens total scheduling time by about 1.1%, while the optimal task allocation equilibrium scheme reduces task load variance by 82%, enhancing resource utilization and long-term system stability. This research provides a practical framework for airports to enhance ETV scheduling efficiency and achieve sustainable development.","manuscriptTitle":"Research on two-stage optimization model of Electric Towing Vehicles at Airports","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-20 05:47:33","doi":"10.21203/rs.3.rs-7370197/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"51780399-c40d-4ffa-8e8d-114f7915edfa","owner":[],"postedDate":"August 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T14:24:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-20 05:47:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7370197","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7370197","identity":"rs-7370197","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}