@inproceedings{6b093eb1fd64471bae8bec4891aacfe3,
title = "An analysis of evolutionary algorithms based on neighbourhood and step sizes",
abstract = "Evolutionary algorithms (EAs) can be regarded as algorithms based on neighbourhood search, where different search operators (such as crossover and mutation) determine different neighbourhood and step sizes. This paper analyses the efficiency of various mutations in evolutionary programming (EP) by examining their neighbourhood and step sizes. It shows analytically when and why Cauchy mutation-based fast EP (FEP) is better than Gaussian mutation-based classical EP (CEP). It also studies the relationship between the optimality of the solution and the time used to find the solution. Based on the theoretical analysis, an improved FEP (IFEP) is proposed, which combines the advantages of both Cauchy and Gaussian mutations in EP. Although IFEP is very simple and requires no extra parameters, it performs better than both FEP and CEP for a number of benchmark problems. {\textcopyright} Springer-Verlag Berlin Heidelberg 1997.",
keywords = "Global Optimum, Evolutionary Algorithm, Benchmark Problem, Neighbourhood Size, Unimodal Function",
author = "Xin YAO and Guangming LIN and Yong LIU",
year = "1997",
doi = "10.1007/BFb0014820",
language = "English",
isbn = "9783540627883",
series = "Lecture Notes in Computer Science",
publisher = "Springer Berlin Heidelberg",
pages = "297--307",
editor = "ANGELINE, {Peter J.} and REYNOLDS, {Robert G.} and MCDONNELL, { John R.} and Russ EBERHART",
booktitle = "Evolutionary Programming VI : 6th International Conference, EP 97, Indianapolis, Indiana, USA, April 13-16, 1997, Proceedings",
}