Exposing the grey wolf, moth?flame, whale, firefly, bat, and antlion algorithms: six misleading optimization techniques inspired by<i>bestial</i>metaphors

We present a rigorous, component-based analysis of six widespread metaphor-based algorithms for tackling continuous optimization problems. In addition to deconstructing the into their components and relating them with equivalent proposed in well-established techniques, such as particle swarm evolutionary algorithms, we analyze use metaphors that inspired these understand whether usage has brought any novel useful concepts field metaheuristics. Our result is ideas studied have been literature metaheuristics years only novelty self-proclaimed different terminologies derived from new metaphors. discuss reasons why are misleading ultimately useless source inspiration design effective tools. Finally, rationale often presented by authors motivation propose more this type, which based on wrong understanding no-free-lunch theorems optimization.