Reliability Redundancy Allocation for Fire Extinguisher Drone using Hybrid PSO-GWO

Reliability Redundancy Allocation for Fire Extinguisher Drone using Hybrid PSO-GWO | 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 Reliability Redundancy Allocation for Fire Extinguisher Drone using Hybrid PSO-GWO Ashok Singh Bhandari, Akshay Kumar, Mangey Ram This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1353340/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Jun, 2023 Read the published version in Soft Computing → Version 1 posted 4 You are reading this latest preprint version Abstract Reliability Redundancy Allocation Problem (RRAP) plays a vital role in reliability improvement and designing of any system which depends on the arrangement of components i.e., series, parallel, or complex, reliability of the components, and redundancy allocation for the components. In this work, a Fire Extinguisher Drone (FED) is considered for RRAP. The FEDs are very valuable for firefighters in tackling emergencies in non-reachable areas. To maximize the reliability of FED a non-linear mixed integer programming problem is formulated and optimized using the Hybrid Particle Swarm Grey Wolf Optimizer (HPSGWO). This metaheuristic fuses the Particle Swarm Optimization’s (PSO) exploitation ability with the grey wolf optimizer’s (GWO) exploration ability. With constraints such as cost, weight, and volume for the system, different levels of redundancies are applied to get the best redundancy allocation that maximizes the reliability of FED. Also, the results are of HPSGWO for each allocation are compared with the results of GWO, which clearly explains the superiority of the HPSGWO over GWO as well as PSO. RRAP fire extinguisher drone PSO GWO HPSGWO Full Text Cite Share Download PDF Status: Published Journal Publication published 27 Jun, 2023 Read the published version in Soft Computing → Version 1 posted Reviewers agreed at journal 17 Jan, 2023 Reviewers invited by journal 17 Jan, 2023 Editor assigned by journal 23 Feb, 2022 First submitted to journal 17 Feb, 2022 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-1353340","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":168444424,"identity":"11500fa0-987d-4f14-820f-4007d57c9c3c","order_by":0,"name":"Ashok Singh Bhandari","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-3706-0272","institution":"Graphic Era Deemed to be University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ashok","middleName":"Singh","lastName":"Bhandari","suffix":""},{"id":168444425,"identity":"bc4b373b-fe68-45d7-aed1-7b75791b2752","order_by":1,"name":"Akshay Kumar","email":"","orcid":"","institution":"Graphic Era Hill University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Akshay","middleName":"","lastName":"Kumar","suffix":""},{"id":168444426,"identity":"0374d310-59a7-441d-9c5c-87d2a9456eba","order_by":2,"name":"Mangey Ram","email":"","orcid":"","institution":"Graphic Era Deemed to be University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mangey","middleName":"","lastName":"Ram","suffix":""}],"badges":[],"createdAt":"2022-02-12 14:12:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1353340/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1353340/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00500-023-08560-8","type":"published","date":"2023-06-27T21:25:45+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":44732097,"identity":"2a6c9df2-bb6c-49e4-87bc-d19ae4761b15","added_by":"auto","created_at":"2023-10-16 21:52:54","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":321382,"visible":true,"origin":"","legend":"","description":"","filename":"FiireExtinguisherDroneManuscriptSOCO.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1353340/v1_covered_45acff54-d705-46d5-aacc-ad4156110563.pdf"}],"financialInterests":"","formattedTitle":"Reliability Redundancy Allocation for Fire Extinguisher Drone using Hybrid PSO-GWO","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":true,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"soft-computing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"soco","sideBox":"Learn more about [Soft Computing](https://www.springer.com/journal/500)","snPcode":"500","submissionUrl":"https://submission.nature.com/new-submission/500/3","title":"Soft Computing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"RRAP, fire extinguisher drone, PSO, GWO, HPSGWO","lastPublishedDoi":"10.21203/rs.3.rs-1353340/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1353340/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eReliability Redundancy Allocation Problem (RRAP) plays a vital role in reliability improvement and designing of any system which depends on the arrangement of components i.e., series, parallel, or complex, reliability of the components, and redundancy allocation for the components. 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