The search for powerful optimizers has led to the development of a multitude of metaheuristic algorithms inspired from all areas. This work focuses on the animal kingdom as a source of inspiration and performs an extensive, yet not exhaustive, review of the animal inspired metaheuristics proposed in the 2006–2021 period. The review is organized considering the biological classification of living things, with a breakdown of the simulated behavior mechanisms. The centralized data indicated that 61.6% of the animal-based algorithms are inspired from vertebrates and 38.4% from invertebrates. In addition, an analysis of the mechanisms used to ensure diversity was performed. The results obtained showed that the most frequently used mechanisms belong to the niching category.

中文翻译：

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来自动物王国的元启发式回顾

对强大优化器的搜索导致了从各个领域启发的众多元启发式算法的开发。这项工作侧重于将动物王国作为灵感来源，并对 2006-2021 年期间提出的受动物启发的元启发式进行了广泛但并非详尽的回顾。审查的组织考虑了生物的生物学分类，并对模拟行为机制进行了细分。集中数据表明，61.6% 的基于动物的算法来自脊椎动物，38.4% 来自无脊椎动物。此外，还对用于确保多样性的机制进行了分析。获得的结果表明，最常用的机制属于生态位类别。