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| Content Provider | Springer Nature Link |
|---|---|
| Author | Maruyama, Takashi Kita, Eisuke |
| Copyright Year | 2009 |
| Abstract | The stochastic schemata exploiter (SSE), which is one of the evolutionary algorithms based on schemata theory, was presented by Aizawa. The convergence speed of SSE is much faster than simple genetic algorithm. It sacrifices somewhat the global search performance.This paper describes an improved algorithm of SSE, which is named as cross-generational elitist selection SSE (cSSE). In cSSE, the use of the cross-generational elitist selection enhances the diversity of the individuals in the population and therefore, the global search performance is improved.In the numerical examples, cSSE is compared with genetic algorithm with minimum generation gap (MGG), Bayesian optimization algorithm (BOA), and SSE. The results show that cSSE has fast convergence and good global search performance. |
| Starting Page | 123 |
| Ending Page | 129 |
| Page Count | 7 |
| File Format | |
| ISSN | 16737350 |
| Journal | Frontiers of Computer Science in China |
| Volume Number | 3 |
| Issue Number | 1 |
| e-ISSN | 16737466 |
| Language | English |
| Publisher | SP Higher Education Press |
| Publisher Date | 2009-03-12 |
| Publisher Institution | Chinese Universities |
| Publisher Place | Heidelberg |
| Access Restriction | Subscribed |
| Subject Keyword | stochastic schemata exploiter cross generational elitist selection minimal generation gap Bayesian optimization algorithm Computer Science |
| Content Type | Text |
| Resource Type | Article |
| Subject | Theoretical Computer Science Computer Science |
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