| dc.contributor.author | Krömer, Pavel | |
| dc.contributor.author | Snášel, Václav | |
| dc.contributor.author | Platoš, Jan | |
| dc.contributor.author | Húsek, Dušan | |
| dc.date.accessioned | 2009-04-06T07:11:04Z | |
| dc.date.available | 2009-04-06T07:11:04Z | |
| dc.date.issued | 2009 | |
| dc.identifier.citation | Neural Network World. 2009, vol. 19, issue 1, p. 65-80. | en |
| dc.identifier.issn | 1210-0552 | |
| dc.identifier.uri | http://hdl.handle.net/10084/71256 | |
| dc.description.abstract | inear ordering problem is a well-known optimization problem attractive for its complexity (it is an NP-hard problem), rich library of test data and variety of real world applications. In this paper, we investigate the use and performance of two variants of genetic algorithms, mutation only genetic algorithms and higher level chromosome genetic algorithm, on the linear ordering problem. Both methods are tested and evaluated on a library of real world and artificial linear ordering problem instances. | en |
| dc.language.iso | cs | en |
| dc.publisher | Akademie věd České republiky, Ústav informatiky | en |
| dc.publisher | České vysoké učení technické v Praze. Dopravní fakulta | |
| dc.relation.ispartofseries | Neural Network World | en |
| dc.title | Genetic algorithms for the linear ordering problem | en |
| dc.type | article | en |
| dc.identifier.location | Není ve fondu ÚK | en |
| dc.identifier.wos | 000264426400005 | |