Kangaroo Optimization Algorithm

This paper proposes a novel metaheuristic optimization algorithm based on kangaroo group behavior—the Kangaroo Optimization Algorithm (KOA). By simulating kangaroo behaviors such as foraging, group interactions, juvenile hiding, and mating competition, the algorithm incorporates innovative mechanisms such as a dynamic energy model, an environmental adaptation factor, a juvenile hiding mechanism, a mating competition guidance mechanism, and an adaptive jumping step size. This method achieves a balance between global search and local exploitation capabilities. Compared to traditional metaheuristic algorithms, KOA theoretically possesses stronger diversity maintenance and convergence stability, providing a new approach to solving complex optimization problems.