Brain Drain Optimization (BRADO) Algorithm to Solve Multi-Objective Expert Team Formation Problem in Social Networks

Brain Drain Optimization (BRADO) Algorithm to Solve Multi-Objective Expert Team Formation Problem in Social Networks | 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 Brain Drain Optimization (BRADO) Algorithm to Solve Multi-Objective Expert Team Formation Problem in Social Networks Alireza Basiri, Ellips Masehian, Fattaneh Taghiyareh, Peyman Hosseini This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4265402/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 Team performance and the composition of the members determine the success of a project. The multi-objective expert team formation problem seeks to identify a collaborative and affordable team of experts such that the hiring costs are minimized and mutual communication is maximized given a network of experts and an essential set of skills. A new swarm-based metaheuristic, called BRADO, has been utilized to address this NP-hard problem. The BRADO algorithm emulates the emigration phenomenon of intellectual elites of society. This problem has been solved by considering two different approaches, the Sigma, and the Multiplication methods, for integrating the affordability and collaboration objective functions. The problem has been solved for projects of varying scales by the proposed BRADO, Multi-objective PSO, NSGA-II, and Multi-objective ICA. Our experiments show that BRADO provides more efficient solutions to the multi-objective expert team formation problem than the other algorithms, especially for projects with more required skills. BRADO Affordable and Collaborative Team Formation Social Networks Metaheuristics 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-4265402","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":291646421,"identity":"49f8321b-f78e-4135-847a-d0870b96d28d","order_by":0,"name":"Alireza Basiri","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsklEQVRIiWNgGAWjYBACAyA+wGBgwwPlSxCtJY2HgY0ULUBwmAGqhQhgzn784eGKgvMyBvcbGD/8YLDIJ6jFsifH4OAZg9s8BscYmCV7GCQsGwg67EAOw8EGiBYGaaBfDAjaYnD++QOglnNgW34Tp+VGggFQywGQFjbibLGc8QakJZlH8lhim2WPARFazPnTH39s+GNnz3f48OEbPyrqCGtBAowN8GgaBaNgFIyCUUAhAADOnjYPnO9x+AAAAABJRU5ErkJggg==","orcid":"","institution":"Isfahan University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Alireza","middleName":"","lastName":"Basiri","suffix":""},{"id":291646422,"identity":"496122b7-cd04-4135-a08c-dec230cadb07","order_by":1,"name":"Ellips Masehian","email":"","orcid":"","institution":"California State Polytechnic University","correspondingAuthor":false,"prefix":"","firstName":"Ellips","middleName":"","lastName":"Masehian","suffix":""},{"id":291646423,"identity":"3dac01a7-d365-4bda-813b-21aa4e40ecc3","order_by":2,"name":"Fattaneh Taghiyareh","email":"","orcid":"","institution":"University of Tehran","correspondingAuthor":false,"prefix":"","firstName":"Fattaneh","middleName":"","lastName":"Taghiyareh","suffix":""},{"id":291646424,"identity":"b36e2df8-4c61-4b49-91cc-7c9a705e911f","order_by":3,"name":"Peyman Hosseini","email":"","orcid":"","institution":"Queen Mary University of London","correspondingAuthor":false,"prefix":"","firstName":"Peyman","middleName":"","lastName":"Hosseini","suffix":""}],"badges":[],"createdAt":"2024-04-14 14:44:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4265402/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4265402/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57488287,"identity":"55dcc26d-338e-4784-8a1e-878af926bdbf","added_by":"auto","created_at":"2024-05-31 10:49:26","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":940537,"visible":true,"origin":"","legend":"","description":"","filename":"MOBDO.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4265402/v1_covered_7964f203-f4ac-49bc-b453-9051b4c19001.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Brain Drain Optimization (BRADO) Algorithm to Solve Multi-Objective Expert Team Formation Problem in Social Networks","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":"BRADO, Affordable and Collaborative Team Formation, Social Networks, Metaheuristics","lastPublishedDoi":"10.21203/rs.3.rs-4265402/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4265402/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Team performance and the composition of the members determine the success of a project. 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