Ruppell's Fox Optimizer (RFO)

Ruppell's Fox Optimizer: A novel meta-heuristic approach for solving global optimization problems

A new swarm-based, nature-inspired meta-heuristic method, called Ruppell's Fox Optimizer (RFO), is designed and examined in this study to address global optimization problems. RFO takes inspiration from the natural and intelligent communal foraging practices of Ruppell's foxes, both during the day and at night. The optimizer mathematically simulates a variety of chief foraging activities of Ruppell's foxes using their acute eyesight, hearing, and scent to hunt, to accommodate both exploration and exploitation aspects throughout the optimization action. The RFO algorithm simulates the rotating eyes' feature of Ruppell's foxes to a field of view of about 260 degrees, as well as the feature of rotating their ears to a field of hearing of about 150 degrees.