{"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/sorting-by-swaps-with-noisy-comparisons","title":"Sorting by Swaps with Noisy Comparisons","arxiv_id":"1803.04509","date":"2018-03-12","proceeding":null,"authors":["Tomáš Gavenčiak","Barbara Geissmann","Johannes Lengler"],"abstract":"We study sorting of permutations by random swaps if each comparison gives the\nwrong result with some fixed probability $p<1/2$. We use this process as\nprototype for the behaviour of randomized, comparison-based optimization\nheuristics in the presence of noisy comparisons. As quality measure, we compute\nthe expected fitness of the stationary distribution. To measure the runtime, we\ncompute the minimal number of steps after which the average fitness\napproximates the expected fitness of the stationary distribution.\n  We study the process where in each round a random pair of elements at\ndistance at most $r$ are compared. We give theoretical results for the extreme\ncases $r=1$ and $r=n$, and experimental results for the intermediate cases. We\nfind a trade-off between faster convergence (for large $r$) and better quality\nof the solution after convergence (for small $r$).","url_abs":"http://arxiv.org/abs/1803.04509v1","url_pdf":"http://arxiv.org/pdf/1803.04509v1.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":"sorting-by-swaps-with-noisy-comparisons","repo_url":"https://github.com/gavento/swap-sorting-experiments","is_official":1,"mentioned_in_paper":1,"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}