Improve zebra optimization algorithm with adaptive oscillation weight and golden sine operator

Improve zebra optimization algorithm with adaptive oscillation weight and golden sine operator | 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 Improve zebra optimization algorithm with adaptive oscillation weight and golden sine operator Wenmin He, Songyang Ma, Cunsong Wang, Quanling Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3820826/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract The Zebra Optimization Algorithm (ZOA) is a newly proposed heuristic algorithm, which simulates the foraging behavior and defense strategy of zebras in nature. Like other optimization algorithms, ZOA also has some limitations. In this paper, an improved Zebra Optimization Algorithm (IZOA) was proposed. An adaptive oscillation weight is used to replace the random operator of ZOA , enabling the algorithm to adaptively adjust the search space and avoid falling into local optima. Additionally, this paper designs an improved golden sine operator added to ZOA. By using the search characteristics of the sine function and the golden ratio in GoldSA, the algorithm's convergence and optimization accuracy are further improved. The last replacement strategy was formulated to mimic the survival status of zebras in nature, improving the algorithm's search capabilities in complex scenarios. Finally, to assess the optimization performance of IZOA, this paper utilized the 30 benchmark functions in CEC-2017 and three common engineering problems for experiments, and the results clearly demonstrated the significant advantages of IZOA. Zebra Optimization Algorithm heuristic algorithm adaptive oscillation weight Golden Sine Algorithm last replacement strategy Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 14 Feb, 2024 Reviewers agreed at journal 31 Jan, 2024 First submitted to journal 01 Jan, 2024 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-3820826","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":270525339,"identity":"f41fc186-b4a4-4a0d-b9b5-a06d4d79c8bc","order_by":0,"name":"Wenmin He","email":"","orcid":"","institution":"Nanjing Tech University","correspondingAuthor":false,"prefix":"","firstName":"Wenmin","middleName":"","lastName":"He","suffix":""},{"id":270525340,"identity":"32cb8714-b599-40be-b33c-55aafbea2b63","order_by":1,"name":"Songyang Ma","email":"","orcid":"","institution":"Nanjing Tech University","correspondingAuthor":false,"prefix":"","firstName":"Songyang","middleName":"","lastName":"Ma","suffix":""},{"id":270525341,"identity":"9daf81eb-c74b-44ee-9e41-1bbf322231b9","order_by":2,"name":"Cunsong Wang","email":"","orcid":"","institution":"Nanjing Tech University","correspondingAuthor":false,"prefix":"","firstName":"Cunsong","middleName":"","lastName":"Wang","suffix":""},{"id":270525342,"identity":"974317da-d8d3-44d0-8c5d-8fcdf791ea1f","order_by":3,"name":"Quanling Zhang","email":"data:image/png;base64,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","orcid":"","institution":"Nanjing Tech University","correspondingAuthor":true,"prefix":"","firstName":"Quanling","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2023-12-29 10:34:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3820826/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3820826/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50646527,"identity":"c2861072-5986-4d34-86a2-faa64ea0a1fd","added_by":"auto","created_at":"2024-02-05 07:39:26","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":528325,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3820826/v1_covered_444076e6-1f09-441e-aff3-9d78f49d3250.pdf"}],"financialInterests":"","formattedTitle":"Improve zebra optimization algorithm with adaptive oscillation weight and golden sine operator","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"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":"Zebra Optimization Algorithm, heuristic algorithm, adaptive oscillation weight, Golden Sine Algorithm, last replacement strategy","lastPublishedDoi":"10.21203/rs.3.rs-3820826/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3820826/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The Zebra Optimization Algorithm (ZOA) is a newly proposed heuristic algorithm, which simulates the foraging behavior and defense strategy of zebras in nature. Like other optimization algorithms, ZOA also has some limitations. In this paper, an improved Zebra Optimization Algorithm (IZOA) was proposed. An adaptive oscillation weight is used to replace the random operator of ZOA , enabling the algorithm to adaptively adjust the search space and avoid falling into local optima. Additionally, this paper designs an improved golden sine operator added to ZOA. By using the search characteristics of the sine function and the golden ratio in GoldSA, the algorithm's convergence and optimization accuracy are further improved. The last replacement strategy was formulated to mimic the survival status of zebras in nature, improving the algorithm's search capabilities in complex scenarios. 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