@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},
}