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This article introduces the Fuzzy Hunter Optimizer (FHO), a novelmetaheuristic inspired by L\'evy diffuse visibility walk observed in predatoryspecies and even in human behavior during the search for sustenance. To addressa constrained optimization problem, we initialize a population of hunters inthe search space. The hunter with the best fitness represents the food source.The other hunters move through the search space following a L\'evy walk. Whenthey spot the food source, they move towards it, gradually abandoning the Levywalk. To model the hunters visibility, we employ linear membership functions.In each iteration, the hunter with the best fitness becomes the food source.Unlike other metaheuristics, FHO parameters (visibility functions) do notrequire pre-calibration, since they adapt with iterations.

Fuzzy Hunter Optimizer: An Bio-Metaheuristic Algorithm Inspired by L\'evy Walks