Name
Abstract | ||
|---|---|---|
Genetic algorithms (GAs) are stochastic optimization techniques, and we have studied the effects of stochastic fluctuation in the process of GA evolution. A mathematical study was carried out for GA on OneMax function within the framework of Markov chain model. We treated the task of estimating convergence time of the Markov chain for OneMax problem. Then, in order to study hitting time, we study the state after convergence. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.2991/jrnal.2015.2.2.14 | JOURNAL OF ROBOTICS NETWORKING AND ARTIFICIAL LIFE |
Keywords | Field | DocType |
genetic algorithms,OneMax problem,Markov model,convergence time,hitting time | Convergence (routing),Stochastic optimization,Mathematical optimization,Markov model,Markov chain,Hitting time,Genetic algorithm,Mathematics | Journal |
Volume | Issue | ISSN |
2 | 2 | 2352-6386 |
Citations | PageRank | References |
2 | 0.46 | 3 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| yifei du | 1 | 4 | 0.89 |
| qinlian ma | 2 | 6 | 1.07 |
| Kenji Aoki | 3 | 5 | 3.52 |
| Makoto Sakamoto | 4 | 25 | 16.45 |
| Hiroshi Furutani | 5 | 54 | 22.85 |
| Yu-an Zhang | 6 | 23 | 8.97 |