@inproceedings{cdc36b474cdd4b119df30f08ed8db27d,
title = "Fast evolution strategies",
abstract = "Evolution strategies are a class of general optimisation algorithms which are applicable to functions that are multimodal, non differentiable, or even discontinuous. Although recombination operators have been introduced into evolution strategies, their primary search operator is still mutation. Classical evolution strategies rely on Gaussian mutations. A new mutation operator based on the Cauchy distribution is proposed in this paper. It is shown empirically that the new evolution strategy based on Cauchy mutation outperforms the classical evolution strategy on most of the 23 benchmark problems tested in this paper. These results, along with those obtained by fast evolutionary programming demonstrate that the superiority of Cauchy mutation is not dependent on any particular selection scheme. Cauchy mutation is applicable to a variety of evolutionary algorithms. {\textcopyright} Springer-Verlag Berlin Heidelberg 1997.",
keywords = "Local Minimum, Evolution Strategy, Benchmark Problem, Search Operator, Unimodal Function",
author = "Xin YAO and Yong LIU",
year = "1997",
doi = "10.1007/BFb0014808",
language = "English",
isbn = "9783540627883",
series = "Lecture Notes in Computer Science",
publisher = "Springer Berlin Heidelberg",
pages = "149--161",
editor = "ANGELINE, {Peter J.} and REYNOLDS, {Robert G.} and MCDONNELL, {John R.} and Russ EBERHART",
booktitle = "Evolutionary Programminag VI 6th International Conference, EP 97, Indianapolis, Indiana, USA, April 13-16, 1997, Proceedings",
}