Turing computability of (non-)linear optimization
نویسندگان
چکیده
We consider the classical LINEAR OPTIMIZATION problem, but in the Turing rather than the REAL-RAM 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.
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تاریخ انتشار 2001