Olympic Champion Algorithm (OCA): A new human-inspired metaheuristic algorithm for solving optimization problems

Olympic Champion Algorithm (OCA): A new human-inspired metaheuristic algorithm for solving 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 Olympic Champion Algorithm (OCA): A new human-inspired metaheuristic algorithm for solving optimization problems Daniel Rajabi, HuriyeSadat Sadeghi, Mohammad Bagher Menhaj, Amir Abolfazl Suratgar, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7388693/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 The complexity and computational demands of many optimization challenges have led to the rise and advancement of metaheuristic algorithms. These methods offer intelligent approaches for optimization, utilizing a structured and iterative process to search the solution space effectively. In this paper, we introduce a novel metaheuristic approach known as the Olympic Champion Algorithm (OCA), inspired by human behavior. The fundamental idea behind OCA is inspired by the structured process of transforming an ordinary human into an Olympic champion athlete. This inspiration is drawn from the structure of talent discovery, Coaching and Training, Local Competitions, Global Ambitions and Olympic quota, Social Support, Close Competitions, Resilience and Persistence and Intelligent Analysis of Opponents in Finals employed to choose the champion of each iteration. The implementation stages of OCA are modeled mathematically in three phases: population generation and exploration, exploitation, and description. "The performance of the proposed OCA was evaluated on 140 challenging benchmark functions and 15 well-known engineering design problems. The convergence curves and statistical data were compared with 22 highly cited optimization algorithms. Statistical validation was carried out using the Wilcoxon and Friedman tests. The results demonstrate that the OCA is one of the most powerful and effective metaheuristic optimization algorithms for various problems and applications, highlighting its distinctiveness. The article clearly presents the OCA algorithm, which uses a novel and effective solution update formula to achieve impressive results, and emphasizes its potential to advance future metaheuristic algorithms. Olympic Champion Algorithm Global Optimization Metaheuristic Exploration and Exploitation Benchmark function Optimal design 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-7388693","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":513509563,"identity":"b8fde652-a757-48a5-9d76-a467a1a5116a","order_by":0,"name":"Daniel Rajabi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Rajabi","suffix":""},{"id":513509567,"identity":"af827b0b-1dcf-47f8-a100-f1e073d3b63e","order_by":1,"name":"HuriyeSadat Sadeghi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"HuriyeSadat","middleName":"","lastName":"Sadeghi","suffix":""},{"id":513509568,"identity":"d312884c-4ad8-4c4d-9ab6-d2583fe6d70a","order_by":2,"name":"Mohammad Bagher Menhaj","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"Bagher","lastName":"Menhaj","suffix":""},{"id":513509569,"identity":"60f6acc1-1676-4e4f-a657-313236022c97","order_by":3,"name":"Amir Abolfazl Suratgar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYHAD5gNQBmMDMcoNgJgtgYEhgTQtPAZQLQQAfwP7M+mKmj92/bPPfPzM+4NBnr+Bue0DPi0SB3jMJM8cM0iecS53szRPAoPhjAOMzTPwWnP/DZtkA5tBMsMZ3g0gLYwbGBib8eqQP8D+TLLhn0Gy/Bmex7+BWuwJajE4wGAm2dhmYGdwhocNZEsiQS2GB3iMLRv7jBMMz7CZWc5Jk0iecZiAFrkD7A9vNnyTs5c7w/z4xhsbG9v+9vbHeLXAQGIDhJYApgKiNDAw2BOpbhSMglEwCkYiAAACKkB80ZOktAAAAABJRU5ErkJggg==","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Amir","middleName":"Abolfazl","lastName":"Suratgar","suffix":""},{"id":513509570,"identity":"3bc9166d-96c3-4a36-b1c9-eb809030b74c","order_by":4,"name":"Seyedali Mirjalili","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Seyedali","middleName":"","lastName":"Mirjalili","suffix":""}],"badges":[],"createdAt":"2025-08-16 16:38:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7388693/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7388693/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":99321008,"identity":"4af06ecd-9c7d-42d0-a25f-30c312a84401","added_by":"auto","created_at":"2025-12-31 16:39:02","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3584226,"visible":true,"origin":"","legend":"","description":"","filename":"OCA11August.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7388693/v1_covered_9b4da6ed-3970-4015-844c-1c41c07f3035.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eOlympic Champion Algorithm (OCA): A new human-inspired metaheuristic algorithm for solving optimization problems\u003c/p\u003e","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":"Olympic Champion Algorithm, Global Optimization, Metaheuristic, Exploration and Exploitation, Benchmark function, Optimal design","lastPublishedDoi":"10.21203/rs.3.rs-7388693/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7388693/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe complexity and computational demands of many optimization challenges have led to the rise and advancement of metaheuristic algorithms. 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