A Generalized Stationary Point Convergence Theory for Evolutionary Algorithms
نویسنده
چکیده
This paper presents a convergence theory for evolutionary pattern search algorithms (EP-SAs). EPSAs are self-adapting evolutionary algorithms that modify the step size of the mutation operator in response to the success of previous optimization steps. Previously, we have proven a stationary point convergence theory for EPSAs for which the step size is not allowed to increase. The present analysis generalizes this analysis to prove a convergence theory for EPSAs that are allowed to both increase and decrease the step size. This convergence theory is based on an extension of the convergence theory for generalized pattern search methods.
منابع مشابه
A Stationary Point Convergence Theory for Evolutionary Algorithms
This paper deenes a class of evolutionary algorithms called evolutionary pattern search algorithms (EPSAs) and analyzes their convergence properties. This class of algorithms is closely related to evolutionary programming, evolution strategie and real-coded genetic algorithms. EPSAs are self-adapting evolutionary algorithms that modify the step size of the mutation operator in response to the s...
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