  Branching bisimilarity is a behavioural equivalence relation on labelled
transition systems that takes internal actions into account. It has the
traditional advantage that algorithms for branching bisimilarity are more
efficient than all algorithms for other weak behavioural equivalences,
especially weak bisimilarity. With $m$ the number of transitions and $n$ the
number of states, the classic $O(m n)$ algorithm was recently replaced by an
$O(m (\log \lvert \mathit{Act}\rvert + \log n))$ algorithm, which is
unfortunately rather complex. This paper combines its ideas with the ideas from
Valmari. This results in a simpler algorithm with complexity $O(m \log n)$.
Benchmarks show that this new algorithm is also faster and often far more
memory efficient than its predecessors. This makes it the best option for
branching bisimulation minimisation and preprocessing for weak bisimulation of
LTSs.
