[{"status":"public","year":"2001","title":"Turing Computability of (Non-)Linear Optimization","author":[{"full_name":"Brattka, Vasco","last_name":"Brattka","first_name":"Vasco"},{"full_name":"Ziegler, Martin","first_name":"Martin","last_name":"Ziegler"}],"date_updated":"2022-01-06T06:53:26Z","page":"181-184","_id":"18168","language":[{"iso":"eng"}],"user_id":"15415","publication":"Proceedings of the 13th Canadian Conference on Computational Geometry (CCCG'01)","citation":{"bibtex":"@inproceedings{Brattka_Ziegler_2001, title={Turing Computability of (Non-)Linear Optimization}, booktitle={Proceedings of the 13th Canadian Conference on Computational Geometry (CCCG’01)}, author={Brattka, Vasco and Ziegler, Martin}, year={2001}, pages={181–184} }","ama":"Brattka V, Ziegler M. Turing Computability of (Non-)Linear Optimization. In: <i>Proceedings of the 13th Canadian Conference on Computational Geometry (CCCG’01)</i>. ; 2001:181-184.","mla":"Brattka, Vasco, and Martin Ziegler. “Turing Computability of (Non-)Linear Optimization.” <i>Proceedings of the 13th Canadian Conference on Computational Geometry (CCCG’01)</i>, 2001, pp. 181–84.","short":"V. Brattka, M. Ziegler, in: Proceedings of the 13th Canadian Conference on Computational Geometry (CCCG’01), 2001, pp. 181–184.","chicago":"Brattka, Vasco, and Martin Ziegler. “Turing Computability of (Non-)Linear Optimization.” In <i>Proceedings of the 13th Canadian Conference on Computational Geometry (CCCG’01)</i>, 181–84, 2001.","ieee":"V. Brattka and M. Ziegler, “Turing Computability of (Non-)Linear Optimization,” in <i>Proceedings of the 13th Canadian Conference on Computational Geometry (CCCG’01)</i>, 2001, pp. 181–184.","apa":"Brattka, V., &#38; Ziegler, M. (2001). Turing Computability of (Non-)Linear Optimization. In <i>Proceedings of the 13th Canadian Conference on Computational Geometry (CCCG’01)</i> (pp. 181–184)."},"abstract":[{"lang":"eng","text":"We consider the classical LINEAR OPTIMIZATION Problem, but in the Turing rather than the RealRAM model. Asking for mere computability of a function's maximum over some closed domain, we show that the common presumptions 'full-dimensional' and `bounded' in fact cannot be omitted: The sound framework of Recursive Analysis enables us to rigorously prove this folkloristic observation! On the other hand, convexity of this domain may be weakened to connectedness, and even NON-linear functions turn out to be effectively optimizable."}],"date_created":"2020-08-24T11:33:12Z","type":"conference","department":[{"_id":"63"}]}]