  Most optimization problems in real life applications are often highly
nonlinear. Local optimization algorithms do not give the desired performance.
So, only global optimization algorithms should be used to obtain optimal
solutions. This paper introduces a new nature-inspired metaheuristic
optimization algorithm, called Hoopoe Heuristic (HH). In this paper, we will
study HH and validate it against some test functions. Investigations show that
it is very promising and could be seen as an optimization of the powerful
algorithm of cuckoo search. Finally, we discuss the features of Hoopoe
Heuristic and propose topics for further studies.
