why DFS is not optimal but BFs is optimal

This is because by optimal strategy they mean the one whose returned solution maximizes the utility.

Regarding this, nothing guarantees that the first solution found by DFS s optimal. Also BFS is not optimal in a general sense, so your statement as-is is wrong.

The main point here is about being guaranteed that a certain search strategy will always return the optimal result. Any strategy might be the best in a given case, but often (especially in AI), you don't know in what specific case you are, at most you have some hypothesis on that case.

However, DFS is optimal when the search tree is finite, all action costs are identical and all solutions have the same length. However limitating this may sound, there is an important class of problems that satisfies these conditions: the CSPs (constraint satisfaction problems). Maybe all the examples you thought about fall in this (rather common) category.

Optimal as in "produces the optimal path", not "is the fastest algorithm possible". When searching a state space for a path to a goal, DFS may produce a much longer path than BFS. Note that BFS is only optimal when actions are unweighted; if different actions have different weights, you need something like A*.