{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/distributed-evolutionary-k-way-node","title":"Distributed Evolutionary k-way Node Separators","arxiv_id":"1702.01692","date":"2017-02-06","proceeding":null,"authors":["Peter Sanders","Christian Schulz","Darren Strash","Robert Williger"],"abstract":"Computing high quality node separators in large graphs is necessary for a\nvariety of applications, ranging from divide-and-conquer algorithms to VLSI\ndesign. In this work, we present a novel distributed evolutionary algorithm\ntackling the k-way node separator problem. A key component of our contribution\nincludes new k-way local search algorithms based on maximum flows. We combine\nour local search with a multilevel approach to compute an initial population\nfor our evolutionary algorithm, and further show how to modify the coarsening\nstage of our multilevel algorithm to create effective combine and mutation\noperations. Lastly, we combine these techniques with a scalable communication\nprotocol, producing a system that is able to compute high quality solutions in\na short amount of time. Our experiments against competing algorithms show that\nour advanced evolutionary algorithm computes the best result on 94% of the\nchosen benchmark instances.","url_abs":"http://arxiv.org/abs/1702.01692v1","url_pdf":"http://arxiv.org/pdf/1702.01692v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"distributed-evolutionary-k-way-node","repo_url":"https://github.com/KaHIP/KaHIP","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}