Hunter prey optimization

version 1.0.0 (2.99 KB) by iraj naruei
Hunter–prey optimization: algorithm and applications


Updated 2 Dec 2021

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This paper proposes a new population-based optimization algorithm called hunter–prey optimizer (HPO). This algorithm is inspired by the behavior of predator animals such as lions, leopards and wolves, and preys such as stag and gazelle. There are many scenarios of animal hunting behavior, and some of them have transformed into optimization algorithms. The scenario used in this paper is different from the scenario of the previous algorithms. In the proposed approach, a prey and predator population, and a predator attacks a prey that moves away from the prey population. The hunter adjusts his position toward this far prey, and the prey adjusts his position toward a safe place. The search agent’s position that was the best value of the fitness function considered a safe place.

Cite As

iraj naruei (2022). Hunter prey optimization (, MATLAB Central File Exchange. Retrieved .

Naruei, Iraj, et al. “Hunter–Prey Optimization: Algorithm and Applications.” Soft Computing, Springer Science and Business Media LLC, Dec. 2021, doi:10.1007/s00500-021-06401-0.

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