Dynamic Neighborhood Structures in Parallel Evolution Strategies
| dc.contributor.author | Mehnen, Jörn | de |
| dc.contributor.author | Rudolph, Günter | de |
| dc.contributor.author | Weinert, Klaus | de |
| dc.date.accessioned | 2004-12-07T08:20:52Z | |
| dc.date.available | 2004-12-07T08:20:52Z | |
| dc.date.created | 2001 | de |
| dc.date.issued | 2001-10-30 | de |
| dc.description.abstract | Parallelizing is a straightforward approach to reduce the total computation time of evolutionary algorithms. Finding an appropriate communication network within spatially structured populations for improving convergence speed and convergence probability is a difficult task. A new method that uses a dynamic communication scheme in an evolution strategy will be compared with conventional static and dynamic approaches. The communication structure is based on a socalled diffusion model approach. The links between adjacent individuals are dynamically chosen according to deterministic or probabilistic rules. Due to self-organization effects, efficient and stable communication structures are established that perform robust and fast on a multimodal test function. | en |
| dc.format.extent | 253429 bytes | |
| dc.format.extent | 669526 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.format.mimetype | application/postscript | |
| dc.identifier.uri | http://hdl.handle.net/2003/5411 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-15247 | |
| dc.language.iso | en | de |
| dc.publisher | Universität Dortmund | de |
| dc.relation.ispartofseries | Reihe Computational Intelligence ; 112 | de |
| dc.subject.ddc | 004 | de |
| dc.title | Dynamic Neighborhood Structures in Parallel Evolution Strategies | en |
| dc.type | Text | de |
| dc.type.publicationtype | report | |
| dcterms.accessRights | open access |