Name
Abstract | ||
|---|---|---|
Population diversity is essential for avoiding premature convergence in genetic algorithms (GAs) and for the effective use of crossover. Yet the dynamics of how diversity emerges in populations are not well understood. We use rigorous runtime analysis to gain insight into population dynamics and GA performance for the (μ + 1) GA and the Jump test function. We show that the interplay of crossover f... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TEVC.2017.2724201 | IEEE Transactions on Evolutionary Computation |
Keywords | Field | DocType |
Sociology,Statistics,Genetic algorithms,Standards,Algorithm design and analysis,Optimization,Computer science | Population,Mathematical optimization,Crossover,Mutation rate,Evolutionary algorithm,Premature convergence,Local optimum,Test functions for optimization,Mathematics,Genetic algorithm | Journal |
Volume | Issue | ISSN |
22 | 3 | 1089-778X |
Citations | PageRank | References |
11 | 0.61 | 23 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Duc-Cuong Dang | 1 | 190 | 13.08 |
| Tobias Friedrich | 2 | 352 | 20.18 |
| Timo Kötzing | 3 | 443 | 38.58 |
| Martin Krejca | 4 | 82 | 9.47 |
| Per Kristian Lehre | 5 | 627 | 42.60 |
| Pietro Simone Oliveto | 6 | 212 | 25.56 |
| Dirk Sudholt | 7 | 1063 | 64.62 |
| Andrew Sutton | 8 | 91 | 9.72 |