{"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/12033097","title":"A Comparative Study of Adaptive Crossover Operators for Genetic Algorithms to Resolve the Traveling Salesman Problem","arxiv_id":"1203.3097","date":"2012-03-14","proceeding":null,"authors":["Otman Abdoun","Jaafar Abouchabaka"],"abstract":"Genetic algorithm includes some parameters that should be adjusting so that\nthe algorithm can provide positive results. Crossover operators play very\nimportant role by constructing competitive Genetic Algorithms (GAs). In this\npaper, the basic conceptual features and specific characteristics of various\ncrossover operators in the context of the Traveling Salesman Problem (TSP) are\ndiscussed. The results of experimental comparison of more than six different\ncrossover operators for the TSP are presented. The experiment results show that\nOX operator enables to achieve a better solutions than other operators tested.","url_abs":"http://arxiv.org/abs/1203.3097v1","url_pdf":"http://arxiv.org/pdf/1203.3097v1.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":"12033097","repo_url":"https://github.com/raissaccorreia/genetic_algorithm","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"traveling-salesman-problem","task_name":"Traveling Salesman Problem"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}