Improved Cuckoo Search Algorithm for Engineering Optimization Problems

Improved Cuckoo Search Algorithm for Engineering Optimization Problems | 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 Improved Cuckoo Search Algorithm for Engineering Optimization Problems Shao-Qiang Ye, Azlan Mohd Zain, Yusliza Yusoff This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6344932/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 paper proposes a grouped dynamic adaptive cuckoo search algorithm (GDACS) to overcome the shortcomings of the standard cuckoo search algorithm (CS), such as poor local search ability, slower search speed in the later stage and low convergence accuracy. The modifications of GDACS could be summarized into two aspects. On the one hand, a chaotic map of the chaotic algorithm is used to generate a chaotic sequence for ensuring the distribution of the initial solution more uniform and increasing the diversity of the solution because of the randomness of initialization. On the other hand, a modified update strategy is discussed to replace the random walk strategy of standard CS by evaluating the fitness value of the bird's nest. According the proposed update strategy, the populations will be grouped due to the pros and cons of fitness, and the different steps strategies are adopted for different groups to realize an adaptive update mechanism. In the experiment part, the optimization of six selected functions is executed to reveal the performance of the proposed GDACS among standard CS, the GDACS, and the other two CS variants. Experiential results and analysis demonstrate that the proposed GDACS has more efficient search performance and more accurate optimization results. Cuckoo search algorithm chaotic transformation population division adaptive update strategy Cauchy distribution Full Text Additional Declarations No competing interests reported. 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-6344932","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":454895225,"identity":"92d76e0b-4be2-4091-b912-02743df9fb60","order_by":0,"name":"Shao-Qiang Ye","email":"data:image/png;base64,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","orcid":"","institution":"Universiti Teknologi Malaysia","correspondingAuthor":true,"prefix":"","firstName":"Shao-Qiang","middleName":"","lastName":"Ye","suffix":""},{"id":454895226,"identity":"c64478b4-9bb4-4e46-b30d-6f74d1588cd4","order_by":1,"name":"Azlan Mohd Zain","email":"","orcid":"","institution":"Universiti Teknologi Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Azlan","middleName":"Mohd","lastName":"Zain","suffix":""},{"id":454895227,"identity":"43dcab52-2df9-479b-9e7d-849d67e08d01","order_by":2,"name":"Yusliza Yusoff","email":"","orcid":"","institution":"Universiti Teknologi Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Yusliza","middleName":"","lastName":"Yusoff","suffix":""}],"badges":[],"createdAt":"2025-03-31 12:53:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6344932/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6344932/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83796527,"identity":"8d03d0f6-1d77-41aa-8423-def4efa53983","added_by":"auto","created_at":"2025-06-03 00:46:37","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":975506,"visible":true,"origin":"","legend":"","description":"","filename":"ImprovedCuckooSearchAlgorithmBasedonEngineeringOptimizationProblems20250315.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6344932/v1_covered_bf866441-6e0f-4b99-b11e-b5ba7d176678.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Improved Cuckoo Search Algorithm for Engineering Optimization Problems","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Cuckoo search algorithm, chaotic transformation, population division, adaptive update strategy, Cauchy distribution","lastPublishedDoi":"10.21203/rs.3.rs-6344932/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6344932/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This paper proposes a grouped dynamic adaptive cuckoo search algorithm (GDACS) to overcome the shortcomings of the standard cuckoo search algorithm (CS), such as poor local search ability, slower search speed in the later stage and low convergence accuracy. 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