85 citations · 897 across the 89 of their papers we have counts for
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Introducing Elitist Black-Box Models: When Does Elitist Selection Weaken the Performance of Evolutionary Algorithms?
Carola Doerr, Johannes Lengler
Black-box complexity theory provides lower bounds for the runtime of black-box optimizers like evolutionary algorithms and serves as an inspiration for the design of new genetic al…
A Tight Runtime Analysis of the Genetic Algorithm on OneMax
Benjamin Doerr, Carola Doerr
Understanding how crossover works is still one of the big challenges in evolutionary computation research, and making our understanding precise and proven by mathematical means mig…
Solving Problems with Unknown Solution Length at (Almost) No Extra Cost
Benjamin Doerr, Carola Doerr, Timo Kötzing
Most research in the theory of evolutionary computation assumes that the problem at hand has a fixed problem size. This assumption does not always apply to real-world optimization…
Optimal Parameter Choices Through Self-Adjustment: Applying the 1/5-th Rule in Discrete Settings
Benjamin Doerr, Carola Doerr
While evolutionary algorithms are known to be very successful for a broad range of applications, the algorithm designer is often left with many algorithmic choices, for example, th…
OneMax in Black-Box Models with Several Restrictions
Carola Doerr, Johannes Lengler
Black-box complexity studies lower bounds for the efficiency of general-purpose black-box optimization algorithms such as evolutionary algorithms and other search heuristics. Diffe…