  Clearing is a niching method inspired by the principle of assigning the
available resources among a niche to a single individual. The clearing
procedure supplies these resources only to the best individual of each niche:
the winner. So far, its analysis has been focused on experimental approaches
that have shown that clearing is a powerful diversity-preserving mechanism.
Using rigorous runtime analysis to explain how and why it is a powerful method,
we prove that a mutation-based evolutionary algorithm with a large enough
population size, and a phenotypic distance function always succeeds in
optimising all functions of unitation for small niches in polynomial time,
while a genotypic distance function requires exponential time. Finally, we
prove that with phenotypic and genotypic distances clearing is able to find
both optima for Twomax and several general classes of bimodal functions in
polynomial expected time. We use empirical analysis to highlight some of the
characteristics that makes it a useful mechanism and to support the theoretical
results.
