Average Drift Analysis and its Application

Drift analysis is a useful tool for estimating the runtime of evolutionary algorithms. A new representation of drift analysis, called average drift analysis, is introduced in this paper. It takes a weaker requirement than point-wise drift analysis does. Point-wise drift theorems are corollaries of average drift theorems. Therefore average drift analysis is more powerful than point-wise drift analysis. To demonstrate the advantage of average drift analysis, we choose a population-based evolutionary algorithms for linear-like functions as a case study. The lower and upper bounds on the runtime have been drawn using average drift analysis. The cut-off points for the OneMax and BinVal are also derived.

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