A Multiobjective Evolutionary Approach to Solving Single-Allocation Hub Median Problem

A Multiobjective Evolutionary Approach to Solving Single-Allocation Hub Median Problem | 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 A Multiobjective Evolutionary Approach to Solving Single-Allocation Hub Median Problem Arup Kumar Bhattacharjee, Anirban Mukhopadhyay This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3887216/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 article presents a multiobjective formulation for the well-known Single-Allocation Hub Median Problem (MO-SA-H-MP). The objective of MO-SA-H-MP is to develop a three-level architecture consisting of demand nodes, hubs, and central hubs, for reducing transportation costs among nodes, while considering two objectives. The first objective is focused on reducing the overheads associated with hubs and central hubs, while the second objective is aimed at reducing transportation costs among nodes. The paper uses two approaches to solve MO-SA-H-MP. The first approach is based on the NSGA-II algorithm, while the second approach uses a Genetic Algorithm (GA) with a local refinement-based technique to solve each objective separately. The resultant network obtained from GA is applied to the other objective, and the solutions of both approaches are compared. The NSGA-II-based approach is found to perform equivalently to the exact method in 48.32% of cases, perform better than the indirect approach of solving each objective separately in more than 81.67% of cases, and have a deviation of less than 10% in 67.50% of cases from the direct approach for solving each objective separately using the Refined GA-based technique. Facility Location Problem Hierarchical Hub Location Problem Multi Objective Single-Allocation Hub Median Problem Genetic Algorithm Non-dominated Sorting Genetic Algorithm-II 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. 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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-3887216","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":268803698,"identity":"0f811c44-61cc-4314-8791-e89499488d52","order_by":0,"name":"Arup Kumar Bhattacharjee","email":"data:image/png;base64,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","orcid":"","institution":"RCC Institute of Information Technology","correspondingAuthor":true,"prefix":"","firstName":"Arup","middleName":"Kumar","lastName":"Bhattacharjee","suffix":""},{"id":268803699,"identity":"cf8e80ae-0b0d-4753-b46c-ae83ad711b4d","order_by":1,"name":"Anirban Mukhopadhyay","email":"","orcid":"","institution":"University of Kalyani","correspondingAuthor":false,"prefix":"","firstName":"Anirban","middleName":"","lastName":"Mukhopadhyay","suffix":""}],"badges":[],"createdAt":"2024-01-22 07:29:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3887216/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3887216/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52811729,"identity":"3e78183b-4832-44ef-8950-f8816dc3c8ae","added_by":"auto","created_at":"2024-03-16 10:01:03","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1133398,"visible":true,"origin":"","legend":"","description":"","filename":"AMultiObjectiveEvolutionaryApproachtoSolvingSAHMP.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3887216/v1_covered_faeae73f-a4d5-4e1a-a03f-0094be3abb37.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Multiobjective Evolutionary Approach to Solving Single-Allocation Hub Median Problem","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":"Facility Location Problem, Hierarchical Hub Location Problem, Multi Objective Single-Allocation Hub Median Problem, Genetic Algorithm, Non-dominated Sorting Genetic Algorithm-II","lastPublishedDoi":"10.21203/rs.3.rs-3887216/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3887216/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis article presents a multiobjective formulation for the well-known Single-Allocation Hub Median Problem (MO-SA-H-MP). 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