Authors: Rudolph, Günter
Title: Self-Adaptation and Global Convergence : A Counter-Example
Language (ISO): en
Abstract: The self-adaptation of the mutation distribution is a distinguishing feature of evolutionary algorithms that optimize over continuous variables. It is widely recognized that self-adaptation accelerates the search for optima and enhances the ability to locate optima accurately, but it is generally unclear whether these optima are global ones or not. Here, it is proven that the probability of convergence to the global optimum is less than one in general even if the objective function is continuous.
URI: http://hdl.handle.net/2003/5368
http://dx.doi.org/10.17877/DE290R-15293
Issue Date: 2001-10-16
Publisher: Universität Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 531

Files in This Item:
File Description SizeFormat 
ci59.pdfDNB89.23 kBAdobe PDFView/Open
ci59.ps117.23 kBPostscriptView/Open


This item is protected by original copyright



All resources in the repository are protected by copyright.