Abstract
We extend the theory of non-elitist evolutionary algorithms (EAs) by considering the offspring population size in the (1,λ) EA. We establish a sharp threshold at λ = log{\frac{e}{e-1}} n ≈5 log10 n between exponential and polynomial running times on OneMax. For any smaller value, the (1,λ) EA needs exponential time on every function that has only one global optimum. We also consider arbitrary unimodal functions and show that the threshold can shift towards larger offspring population sizes. Finally, we investigate the relationship between the offspring population size and arbitrary mutation rates on OneMax. We get sharp thresholds for λ that decrease with the mutation rate. This illustrates the balance between selection and mutation.
Original language | English |
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Pages | 1349-1356 |
DOIs | |
Publication status | Published - 2012 |
Event | 14th International Conference on Genetic and Evolutionary Computation - GECCO 12 - Philadelphia, United States Duration: 7 Jul 2012 → 11 Jul 2012 |
Conference
Conference | 14th International Conference on Genetic and Evolutionary Computation - GECCO 12 |
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Country/Territory | United States |
City | Philadelphia |
Period | 7/07/12 → 11/07/12 |
Keywords
- Evolutionary algorithms
- comma strategies
- offspring populations
- runtime analysis
- drift analysis
- theory