Optimization Algorithm Inspired by Grassland Ecology

Grassland ecosystems are open ecosystems dominated by herbaceous plants and rich in animal and microbial diversity. Their unique sparse distribution, clustered aggregation, seasonal disturbances, and dynamic food web mechanisms provide rich insights for optimization algorithms. This paper proposes a heuristic optimization algorithm based on grassland ecosystems. This algorithm simulates the herbaceous plants, herbivores, carnivores, decomposers, and fire disturbance mechanisms in grasslands, mapping these mechanisms into a solution update strategy for the optimization problem. The algorithm achieves a balance between exploration and utilization while maintaining solution diversity through local search within clusters, inter-cluster migration, dynamic regulation of predation and replenishment, nutrient recirculation by decomposers, and periodic global perturbations. This paper describes the algorithm's mathematical model and formulas in detail in plain text, demonstrating the ecological inspiration and innovative nature of the algorithm's mechanism.