@inproceedings{18168,
abstract = {{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.}},
author = {{Brattka, Vasco and Ziegler, Martin}},
booktitle = {{Proceedings of the 13th Canadian Conference on Computational Geometry (CCCG'01)}},
pages = {{181--184}},
title = {{{Turing Computability of (Non-)Linear Optimization}}},
year = {{2001}},
}