Blue-eared Hedgehog Optimization (BEHO): A Nature-inspired Metaheuristic for Robust and Efficient Global Optimization
Dinler Ö.B. Bektemyssova G. Ahmed M.A. Ibraheem I.K. Smerat A. Montazeri Z. Dehghani M. Malik O.P. Sahin C.B. Al-Salih A.A.M.M. Eguchi K.
31 December 2025Intelligent Network and Systems Society
International Journal of Intelligent Engineering and Systems
2025#18Issue 11133 - 148 pp.
A novel metaheuristic algorithm named the Blue-Eared Hedgehog Optimization (BEHO), inspired by the unique foraging and defensive behaviour of the blue-eared hedgehog is introduced in this study. Unlike conventional optimization methods, BEHO simulates the species’ natural strategies-nocturnal cautious exploration, gradual environmental mapping, and protective retreat-into computational operators that effectively balance exploration and exploitation. The algorithm initializes a diverse population of candidate solutions, simulates hedgehog-inspired gradual movements for exploration, and employs defensive-inspired refinement for exploitation, ensuring robust convergence and preservation of high-quality solutions. BEHO’s performance has been rigorously evaluated on 23 standard benchmark functions, including unimodal, high-dimensional multimodal, and fixed-dimensional multimodal problems, and compared with nine state-of-the-art metaheuristics, including MOA, WaOA, AOA, GWO, LSA, SWO, TLBO, BaOA, and WSO. Experimental results demonstrate that BEHO consistently achieves superior accuracy, stability, and convergence speed across all function categories. Its hedgehog-inspired mechanisms allow the algorithm to escape local optima, maintain population diversity, and achieve precise global solutions in complex and high-dimensional landscapes. The findings highlight BEHO as a highly effective and versatile optimization tool, providing a biologically grounded and computationally efficient framework for solving diverse complex problems.
Blue-eared hedgehog , Exploitation , Exploration , Global convergence , High-dimensional problems , Metaheuristic , Optimization algorithm
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Faculty of Computer Engineering, Siirt University, Siirt, 56100, Turkey
Department of Computer Engineering, International Information Technology University, Almaty, 050000, Kazakhstan
Department of Medical Instrumentation Techniques Engineering, College of Medical Techniques, Al-Farahidi University, Baghdad, 10001, Iraq
Department of Electrical Engineering, College of Engineering, University of Baghdad, Baghdad, 10001, Iraq
Department of Electrical Engineering Techniques, Al Hikma University College, Baghdad, 10001, Iraq
Faculty of Educational Sciences, Al-Ahliyya Amman University, Amman, 19328, Jordan
Centre for Research Impact and Outcome, Chitkara University, Punjab, India
Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, 7155713876, Iraq
Department of Electrical and Software Engineering, University of Calgary, Calgary, T2N 1N4, AB, Canada
Software Engineering Department, Faculty of Engineering and Natural Sciences, Malatya Turgut Ozal University, Malatya, Turkey
Department of Computer Engineering Techniques, Al-Nukhba University College, Baghdad, 10013, Iraq
Department of Information Electronics, Fukuoka Institute of Technology, Iraq
Faculty of Computer Engineering
Department of Computer Engineering
Department of Medical Instrumentation Techniques Engineering
Department of Electrical Engineering
Department of Electrical Engineering Techniques
Faculty of Educational Sciences
Centre for Research Impact and Outcome
Department of Electrical and Electronics Engineering
Department of Electrical and Software Engineering
Software Engineering Department
Department of Computer Engineering Techniques
Department of Information Electronics
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