The entire field of metaheuristics is in dire need of a shakeup. Many of the newer publications are not actually novel [0, 1, 2, 3, 4, 5], the metaphors used to describe these methods only disguise their inner workings and similarities and differences to existing approaches and shouldn't justify their publication [6, 7]. The set of benchmarks used to verify the excellent performance of these methods is small and biased [8, 9]. The metaphors don't match the given algorithms [10], the given algorithms don't match the implementation [11] and the results don't match the implementation [12].

It's junk science with the goal of increasing the authors citation count. One of the most prolific authors of papers on "bioinspired metaheuristics" (Seyedali Mirjalili) manages to publish several dozens of papers every year, some gathering thousands if not tens of thousands of citations.

[0]: https://doi.org/10.4018/jamc.2010040104

[1]: https://doi.org/10.1016/j.ins.2010.12.006

[2]: https://doi.org/10.1016/j.ins.2014.01.026

[3]: https://doi.org/10.1007/s11721-019-00165-y

[4]: https://doi.org/10.1007/978-3-030-60376-2_10

[5]: https://doi.org/10.1016/j.cor.2022.105747

[6]: https://doi.org/10.1111/itor.12001

[7]: https://doi.org/10.1007/s11721-021-00202-9

[8]: https://doi.org/10.1038/s42256-022-00579-0

[9]: https://doi.org/10.48550/arXiv.2301.01984

[10]: https://doi.org/10.1007/s11047-012-9322-0

[11]: https://doi.org/10.1016/j.eswa.2021.116029

[12]: https://doi.org/10.1111/itor.12443