Amine Bendahmane1* and Redouane Tlemsani1

Amine Bendahmane1* and Redouane Tlemsani1 | 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Article Amine Bendahmane1* and Redouane Tlemsani1 Amine Bendahmane, Redouane Tlemsani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1680552/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Butterfly Optimization Algorithm (BOA) is a recent metaheuristic that has been used in several optimization problems. In this paper, we adapt this metaheuristic to robotics for solving the Unknown Area Exploration problem with energy constraints in both single and multi-robot scenarios. We conducted several experiments to validate the approach and compare its performance to well-known metaheuristics used in the literature using 5 different comparison criteria. We also proposed a new version of the algorithm (xBOA) based on the crossover operator. We compared its results to the original BOA and 3 other variants recently introduced in the literature. Although BOA and xBOA are not optimal in all evaluation criteria, we found that BOA can be a good alternative to many metaheuristics in terms of the exploration time, while xBOA is more robust to local optima; has better fitness convergence; and achieves better exploration rates than the original BOA and its other variants. Robotics exploration Butterfly Optimization Algorithm crossover operator metaheuristics multi-robot systems Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 23 May, 2022 Reviewers invited by journal 23 May, 2022 Editor assigned by journal 21 May, 2022 First submitted to journal 11 Oct, 2021 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-1680552","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":108011267,"identity":"784da260-bd64-4fc0-970b-c08ecfecbae7","order_by":0,"name":"Amine Bendahmane","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-7540-1883","institution":"Universite des Sciences et de la Technologie d'Oran Mohamed Boudiaf","correspondingAuthor":true,"prefix":"","firstName":"Amine","middleName":"","lastName":"Bendahmane","suffix":""},{"id":108011268,"identity":"b45b3993-dafd-4c0d-812d-18323d76579c","order_by":1,"name":"Redouane Tlemsani","email":"","orcid":"","institution":"Universite des Sciences et de la Technologie d'Oran Mohamed Boudiaf","correspondingAuthor":false,"prefix":"","firstName":"Redouane","middleName":"","lastName":"Tlemsani","suffix":""}],"badges":[],"createdAt":"2022-05-21 22:33:44","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1680552/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1680552/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":21882075,"identity":"80b0223e-32e3-4792-9ea3-84c668eec060","added_by":"auto","created_at":"2022-05-25 16:53:18","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3292923,"visible":true,"origin":"","legend":"","description":"","filename":"SOCOD2103767reviewer.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1680552/v1_covered.pdf"}],"financialInterests":"","formattedTitle":"Amine Bendahmane1* and Redouane Tlemsani1","fulltext":[{"header":"Full Text","content":"This preprint is available for \u003ca href='/article/rs-1680552/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e."}],"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":false,"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":"Robotics, exploration, Butterfly Optimization Algorithm, crossover operator, metaheuristics, multi-robot systems","lastPublishedDoi":"10.21203/rs.3.rs-1680552/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1680552/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Butterfly Optimization Algorithm (BOA) is a recent metaheuristic that has been used in several optimization problems. 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