Computer Science – Neural and Evolutionary Computing
Scientific paper
2012-02-23
Computer Science
Neural and Evolutionary Computing
accepted to Congress on Evolutionary Computation (WCCI/CEC) 2012
Scientific paper
In this article we present an Elitism Levels Traverse Mechanism that we designed to find bounds on population-based Evolutionary algorithms solving unimodal functions. We prove its efficiency theoretically and test it on OneMax function deriving bounds c{\mu}n log n - O({\mu} n). This analysis can be generalized to any similar algorithm using variants of tournament selection and genetic operators that flip or swap only 1 bit in each string.
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