Big-O notation for lower bound instead of Big-Omega
If you consider the problem Tree traversal, then the correct answer is indeed:

Traversal requires $\Omega$(n) time, since it must visit every node.

We are here talking about requirement and lower bound, as in &quot;what is necessary&quot;.
If you want to talk about common algorithms for tree traversal, then it is true that they also have a complexity $O(n)$, which means that it is an upper bound in &quot;what we can do&quot;.
However, since your question, the wikipedia page was modified and the current sentence does not really make any sense (basically &quot;Tree traversal is $O(n)$. Since it is also $O(n)$, it is optimal.&quot;).