Greater Cane Rat Algorithm (GCRA)

Greater Cane Rat Algorithm: A Nature-Inspired Metaheuristic for Global Optimization Problems

The Greater Cane Rat Algorithm (GCRA) is a novel metaheuristic algorithm inspired by the foraging and mating behaviors of greater cane rats. During exploration, the Greater Cane Rat leave trails while foraging that help locate food/water/shelter. Dominant males retain trail information and others update positions accordingly. In exploitation, Greater Cane Rat concentrate foraging near abundant food when separated during breeding season. GCRA mathematically models these intelligent behaviors for optimization. The implemented optimizer is tested on benchmark functions, complex/real-world problems, and classic engineering problems. Results show GCRA finds optimal/near-optimal solutions, outperforming other algorithms by avoiding local minima. Statistical analyses confirm its superior efficacy and stability over a competitive set of optimization techniques.