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Nature inspired optimization algorithms or simply variations of metaheuristics?
Artificial Intelligence Review ( IF 10.7 ) Pub Date : 2020-08-24 , DOI: 10.1007/s10462-020-09893-8
Alexandros Tzanetos , Georgios Dounias

In the last decade, we observe an increasing number of nature-inspired optimization algorithms, with authors often claiming their novelty and their capabilities of acting as powerful optimization techniques. However, a considerable number of these algorithms do not seem to draw inspiration from nature or to incorporate successful tactics, laws, or practices existing in natural systems, while also some of them have never been applied in any optimization field, since their first appearance in literature. This paper presents some interesting findings that have emerged after the extensive study of most of the existing nature-inspired algorithms. The need for irrationally introducing new nature inspired intelligent (NII) algorithms in literature is also questioned and possible drawbacks of NII algorithms met in literature are discussed. In addition, guidelines for the development of new nature-inspired algorithms are proposed, in an attempt to limit the misleading appearance of variation of metaheuristics as nature inspired optimization algorithms.

中文翻译:

自然启发的优化算法还是元启发式的简单变体?

在过去的十年中,我们观察到越来越多的受自然启发的优化算法,作者经常声称它们的新颖性和作为强大优化技术的能力。然而,这些算法中有相当一部分似乎并没有从自然中汲取灵感,也没有结合自然系统中存在的成功策略、规律或实践,而且其中一些算法自首次出现以来从未应用于任何优化领域。文学。本文介绍了一些有趣的发现,这些发现是在对大多数现有的受自然启发的算法进行广泛研究后出现的。在文献中不合理地引入新的自然启发智能 (NII) 算法的必要性也受到质疑,并讨论了文献中遇到的 NII 算法的可能缺点。此外,
更新日期:2020-08-24
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