Abstract: To gain a better theoretical understanding of how evolutionary algorithms (EAs) cope with plateaus of constant fitness, we propose the n -dimensional Plateau k function as natural benchmark and analyze how different variants of the (1 + 1) EA optimize it. The Plateau k function has a plateau of second-best fitness in a ball of radius k around the optimum. As evolutionary algorithm, we regard the (1 + 1) EA using an arbitrary unbiased mutation operator. Denoting by α the random number of bits flipped in an application of this operator and assum...
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Topics: 
Algorithm
Combinatorics
Mathematical optimization