2012/11/24 by M. A. El-Dosuky, A. H. El-Bassiouny, El-Dosuky, Mohammed +4
Computer Science · Engineering · #Artificial Immune Systems Applications #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Metaheuristic Optimization Algorithms Research #Neural and Evolutionary Computing (cs.NE) #Robotic Path Planning Algorithms
paper · pdf · doi:10.48550/arxiv.1211.6410
openalex publication_date 2012/11/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.