{"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/finding-near-optimal-independent-sets-at","title":"Finding Near-Optimal Independent Sets at Scale","arxiv_id":"1509.00764","date":"2015-09-02","proceeding":null,"authors":["Sebastian Lamm","Peter Sanders","Christian Schulz","Darren Strash","Renato F. Werneck"],"abstract":"The independent set problem is NP-hard and particularly difficult to solve in\nlarge sparse graphs. In this work, we develop an advanced evolutionary\nalgorithm, which incorporates kernelization techniques to compute large\nindependent sets in huge sparse networks. A recent exact algorithm has shown\nthat large networks can be solved exactly by employing a branch-and-reduce\ntechnique that recursively kernelizes the graph and performs branching.\nHowever, one major drawback of their algorithm is that, for huge graphs,\nbranching still can take exponential time. To avoid this problem, we\nrecursively choose vertices that are likely to be in a large independent set\n(using an evolutionary approach), then further kernelize the graph. We show\nthat identifying and removing vertices likely to be in large independent sets\nopens up the reduction space---which not only speeds up the computation of\nlarge independent sets drastically, but also enables us to compute high-quality\nindependent sets on much larger instances than previously reported in the\nliterature.","url_abs":"http://arxiv.org/abs/1509.00764v1","url_pdf":"http://arxiv.org/pdf/1509.00764v1.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":"finding-near-optimal-independent-sets-at","repo_url":"https://github.com/karlsruhemis/kamis","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1509.00764","atlas_url":"https://app.syntology.ai/?focus=1509.00764","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}