Name
Abstract | ||
|---|---|---|
Understanding how the time complexity of evolutionary algorithms (EAs) depend on their parameter settings and characteristics of fitness landscapes is a fundamental problem in evolutionary computation. Most rigorous results were derived using a handful of key analytic techniques, including drift analysis. However, since few of these techniques apply effortlessly to population-based EAs, most time ... |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TEVC.2017.2753538 | IEEE Transactions on Evolutionary Computation |
Keywords | DocType | Volume |
Sociology,Statistics,Genetic algorithms,Runtime,Algorithm design and analysis,Upper bound,Optimization | Journal | 22 |
Issue | ISSN | Citations |
5 | 1089-778X | 13 |
PageRank | References | Authors |
0.68 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dogan Corus | 1 | 57 | 5.79 |
| Duc-Cuong Dang | 2 | 190 | 13.08 |
| Anton V. Eremeev | 3 | 118 | 17.56 |
| Per Kristian Lehre | 4 | 627 | 42.60 |