{"department":[{"_id":"819"}],"keyword":["2-opt","90B06","Classification","Feature selection","MARS","TSP"],"type":"journal_article","volume":69,"citation":{"short":"O. Mersmann, B. Bischl, H. Trautmann, M. Wagner, J. Bossek, F. Neumann, Annals of Mathematics and Artificial Intelligence 69 (2013) 151–182.","ama":"Mersmann O, Bischl B, Trautmann H, Wagner M, Bossek J, Neumann F. A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesperson Problem. Annals of Mathematics and Artificial Intelligence. 2013;69(2):151–182. doi:10.1007/s10472-013-9341-2","ieee":"O. Mersmann, B. Bischl, H. Trautmann, M. Wagner, J. Bossek, and F. Neumann, “A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesperson Problem,” Annals of Mathematics and Artificial Intelligence, vol. 69, no. 2, pp. 151–182, 2013, doi: 10.1007/s10472-013-9341-2.","bibtex":"@article{Mersmann_Bischl_Trautmann_Wagner_Bossek_Neumann_2013, title={A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesperson Problem}, volume={69}, DOI={10.1007/s10472-013-9341-2}, number={2}, journal={Annals of Mathematics and Artificial Intelligence}, author={Mersmann, Olaf and Bischl, Bernd and Trautmann, Heike and Wagner, Markus and Bossek, Jakob and Neumann, Frank}, year={2013}, pages={151–182} }","chicago":"Mersmann, Olaf, Bernd Bischl, Heike Trautmann, Markus Wagner, Jakob Bossek, and Frank Neumann. “A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesperson Problem.” Annals of Mathematics and Artificial Intelligence 69, no. 2 (2013): 151–182. https://doi.org/10.1007/s10472-013-9341-2.","mla":"Mersmann, Olaf, et al. “A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesperson Problem.” Annals of Mathematics and Artificial Intelligence, vol. 69, no. 2, 2013, pp. 151–182, doi:10.1007/s10472-013-9341-2.","apa":"Mersmann, O., Bischl, B., Trautmann, H., Wagner, M., Bossek, J., & Neumann, F. (2013). A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesperson Problem. Annals of Mathematics and Artificial Intelligence, 69(2), 151–182. https://doi.org/10.1007/s10472-013-9341-2"},"user_id":"102979","publication_identifier":{"issn":["1012-2443"]},"year":"2013","author":[{"first_name":"Olaf","full_name":"Mersmann, Olaf","last_name":"Mersmann"},{"full_name":"Bischl, Bernd","last_name":"Bischl","first_name":"Bernd"},{"first_name":"Heike","full_name":"Trautmann, Heike","last_name":"Trautmann"},{"first_name":"Markus","full_name":"Wagner, Markus","last_name":"Wagner"},{"full_name":"Bossek, Jakob","last_name":"Bossek","first_name":"Jakob","id":"102979","orcid":"0000-0002-4121-4668"},{"first_name":"Frank","last_name":"Neumann","full_name":"Neumann, Frank"}],"doi":"10.1007/s10472-013-9341-2","date_created":"2023-11-14T15:58:59Z","status":"public","_id":"48889","abstract":[{"lang":"eng","text":"Meta-heuristics are frequently used to tackle NP-hard combinatorial optimization problems. With this paper we contribute to the understanding of the success of 2-opt based local search algorithms for solving the traveling salesperson problem (TSP). Although 2-opt is widely used in practice, it is hard to understand its success from a theoretical perspective. We take a statistical approach and examine the features of TSP instances that make the problem either hard or easy to solve. As a measure of problem difficulty for 2-opt we use the approximation ratio that it achieves on a given instance. Our investigations point out important features that make TSP instances hard or easy to be approximated by 2-opt."}],"publication":"Annals of Mathematics and Artificial Intelligence","title":"A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesperson Problem","date_updated":"2023-12-13T10:50:41Z","issue":"2","intvolume":" 69","language":[{"iso":"eng"}],"page":"151–182"}