Priority-Based Genetic Algorithm for theClustered Steiner Tree Problem

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This paper introduces a Priority-Based Genetic Algorithm to solve the Clustered Steiner Tree Problem, outperforming existing methods in both metric and non-metric cases by balancing exploration and exploitation.

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Abstract

In a complex network connecting many devices, a set of nodes might be partitioned into multiple local clusters with different functions, properties, or communication protocols. Thus, there has been a rise in network design problems with additional constraints regarding the clustering of vertices, one of them being the Clustered Steiner Tree Problem - a variant of the Steiner Tree Problem. In the literature, there have been a few research working on this problem, but either they only solve it in a metric case, or their exploration capability is still limited. Therefore, their results are not actually good in many cases. To overcome the drawbacks, we propose a Priority-Based Genetic Algorithm to solve the Clustered Steiner Tree Problem. The proposed algorithm maintains a balance between exploration and exploitation to prevent the search from local optima. Experiments and comparisons to existing works in non-metric and metric cases are carried out deliberately to prove the remarkable performance of the proposed algorithm.
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Thus, there has been a rise in network design problems with additional constraints regarding the clustering of vertices, one of them being the Clustered Steiner Tree Problem - a variant of the Steiner Tree Problem. In the literature, there have been a few research working on this problem, but either they only solve it in a metric case, or their exploration capability is still limited. Therefore, their results are not actually good in many cases. To overcome the drawbacks, we propose a Priority-Based Genetic Algorithm to solve the Clustered Steiner Tree Problem. The proposed algorithm maintains a balance between exploration and exploitation to prevent the search from local optima. Experiments and comparisons to existing works in non-metric and metric cases are carried out deliberately to prove the remarkable performance of the proposed algorithm. Genetic Algorithm Clustered Steiner Tree Problem 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-3507907","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":243902303,"identity":"cac23fcc-f75e-4924-b790-2807d2799031","order_by":0,"name":"Tuan-Anh Do","email":"","orcid":"","institution":"Hanoi University of Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tuan-Anh","middleName":"","lastName":"Do","suffix":""},{"id":243902304,"identity":"31c07710-2de4-4e4e-9d17-1abb88d1fbbe","order_by":1,"name":"Ha-Bang 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