Analysis and parameter selection for an Adaptive Random Search algorithm


This paper presents an analysis of an adaptive random search (ARS) algorithm, a global minimization method. A probability model is introduced to characterize the statistical properties of the number of iterations required to find an acceptable solution. Moreover, based on this probability model, a new stopping criterion is introduced to predict the maximum… (More)
DOI: 10.1016/j.matcom.2004.10.002


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