On the analysis of the (1+1) evolutionary algorithm

By Stefan Droste, T. Jansen, I. Wegener. Theoretical Computer Science, 2002

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On the deleterious effects of a priori objectives on evolution and representation (2011, background): “This insight is sobering because the vast majority of empirical experiments in EC assess their results based on benchmarks with a priori objectives [2, 8, 13, 20, 24, 27] and theory often focuses on whether targets can be reached [3, 17].”
A Tutorial on Evolutionary Multiobjective Optimization (2004, methodology): “[37], and Droste, Jansen, and Wegener [8, 9]; a methodological overview is given in [36].”
An efficient, adaptive parameter variation scheme for metaheuristics based on the epsilon-constraint method (2006, background): “The example problem is a bi-objective generalization of the BINARY VALUE (BV) problem proposed in [4] for the complexity analysis of evolutionary algorithms.”
Multiplicative Drift Analysis (2010, methodology): “Afterwards, various methods (variants of Wald’s identity in [11, 19] and Markov’s inequality in [2, 23]) are used to show that the expected stopping time E[T ] is indeed in this regime.”
A Multi-Facet Survey on Memetic Computation (2011, background): “Study conducted to examine the effect of this design issue had confirmed its significant impact on search performances [142].”