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 proposes a new nature-inspired metaheuristic optimization algorithm, called Hoopoe Heuristic (HH).



It is inspired the foraging of Hoopoes .

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-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 proposes a new nature-inspired metaheuristic optimization algorithm, called Hoopoe Heuristic (HH).



It is inspired　the foraging of Hoopoes .

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