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It is quite usual when an evolutionary algorithm tool or library uses alanguage other than C, C++, Java or Matlab that a reviewer or the audiencequestions its usefulness based on the speed of those other languages,purportedly slower than the aforementioned ones. Despite speed being noteverything needed to design a useful evolutionary algorithm application, inthis paper we will measure the speed for several very basic evolutionaryalgorithm operations in several languages which use different virtual machinesand approaches, and prove that, in fact, there is no big difference in speedbetween interpreted and compiled languages, and that in some cases, interpretedlanguages such as JavaScript or Python can be faster than compiled languagessuch as Scala, making them worthy of use for evolutionary algorithmexperimentation.

There is no fast lunch: an examination of the running speed of evolutionary algorithms in several languages