Comprehensive Taxonomies of Nature- and Bio-inspired Optimization Algorithms: Inspiration, Behavior, Critical Analysis, and Recommendations (2020-2024)

This study presents two comprehensive taxonomies to classify nature- and bio-inspired optimization algorithms based on their source of inspiration and algorithmic behavior. The analysis reveals a poor relationship between the natural inspiration and the actual behavior of many algorithms, with over a quarter being versions of classical algorithms. The study provides recommendations to improve research practices in this field.