Felis Catus Optimization (FCO): A novel nature‑inspired metaheuristic algorithm

This study introduces Felis Catus Optimization (FCO), a novel nature‑inspired metaheuristic algorithm modeled on the ecological and adaptive behavioral dynamics of urban domestic cats. FCO divides its population into explorer (male) and exploiter (female) agents to maintain a dynamic equilibrium between global search and local refinement. Male agents perform asynchronous triplet movements governed by adaptive exploration scaling, while female agents execute Gaussian‑based local exploitation and cooperative litter burst. A rejuvenation‑and‑noise ecological cycle replaces explicit renewal events, sustaining diversity and preventing stagnation through random reallocation and mild environmental perturbation. These mechanisms collectively achieve continuous exploration using direct position-update rules. Extensive experiments on CEC 2005 and CEC 2017 benchmarks confirmed FCO’s competitive behavior ranking among top optimizers and outperforming seven algorithms significantly under Holm’s post‑hoc procedure (p