In other words, if the heuristic is consistent, then it implies that A* will expand the optimal number of states.
In other words, if the heuristic is consistent, then it implies that A* will expand the optimal number of states.
Edit: The paper you cited uses a traversal slightly different from traditional A*.
So if you do A* with an inconsistent heuristic, you need to revisit nodes if you explore them a second time with a cheaper cost (i.e., you can re-expand nodes in your closed list). If you do this, you will find optimal solutions even with an inconsistent heuristic.
The only requirement on your heuristic if you A* to find optimal solutions is that it be admissible.
A nitpick: "breadth-first heuristic search" is an algorithm developed by Zhou and Hansen and, while it's related to A* (in that it uses an admissible heuristic to prune the search space), it's not actually a variant of A*. (It's not a best-first search algorithm, since it doesn't expand nodes in increasing order of f cost.)