There is no fast lunch: an examination of the running speed of evolutionary algorithms in several languages
November 03, 2015 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Juan-J. Merelo, Pablo Garcรญa-Sรกnchez, Mario Garcรญa-Valdez, Israel Blancas
arXiv ID
1511.01088
Category
cs.NE: Neural & Evolutionary
Cross-listed
cs.PF
Citations
5
Venue
arXiv.org
Last Checked
4 months ago
Abstract
It is quite usual when an evolutionary algorithm tool or library uses a language other than C, C++, Java or Matlab that a reviewer or the audience questions its usefulness based on the speed of those other languages, purportedly slower than the aforementioned ones. Despite speed being not everything needed to design a useful evolutionary algorithm application, in this paper we will measure the speed for several very basic evolutionary algorithm operations in several languages which use different virtual machines and approaches, and prove that, in fact, there is no big difference in speed between interpreted and compiled languages, and that in some cases, interpreted languages such as JavaScript or Python can be faster than compiled languages such as Scala, making them worthy of use for evolutionary algorithm experimentation.
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