| dc.contributor.author | Krömer, Pavel | |
| dc.contributor.author | Platoš, Jan | |
| dc.contributor.author | Snášel, Václav | |
| dc.date.accessioned | 2020-05-20T08:14:12Z | |
| dc.date.available | 2020-05-20T08:14:12Z | |
| dc.date.issued | 2020 | |
| dc.identifier.citation | Swarm and Evolutionary Computation. 2020, vol. 54, art. no. UNSP 100649. | cs |
| dc.identifier.issn | 2210-6502 | |
| dc.identifier.issn | 2210-6510 | |
| dc.identifier.uri | http://hdl.handle.net/10084/139497 | |
| dc.description.abstract | Halton sequences are d-dimensional quasirandom sequences that fill the d-dimensional hyperspace in a uniform way. They can be used in a variety of applications such as multidimensional integration, uniform sampling, and, e.g., quasi-Monte Carlo simulations. Generalized Halton sequences improve the space-filling properties of original Halton sequences in higher dimensions by digit scrambling. In this work, an evolutionary optimization algorithm, the differential evolution, is used to optimize scrambling permutations of a cl-dimensional generalized Halton sequence so that the discrepancy of the generated point set is minimized. | cs |
| dc.language.iso | en | cs |
| dc.publisher | Elsevier | cs |
| dc.relation.ispartofseries | Swarm and Evolutionary Computation | cs |
| dc.relation.uri | http://doi.org/10.1016/j.swevo.2020.100649 | cs |
| dc.rights | © 2020 Elsevier B.V. All rights reserved. | cs |
| dc.subject | differential evolution | cs |
| dc.subject | combinatorial optimization | cs |
| dc.subject | qasirandom sequences | cs |
| dc.subject | discrepancy | cs |
| dc.title | Differential evolution for the optimization of low-discrepancy generalized Halton sequences | cs |
| dc.type | article | cs |
| dc.identifier.doi | 10.1016/j.swevo.2020.100649 | |
| dc.type.status | Peer-reviewed | cs |
| dc.description.source | Web of Science | cs |
| dc.description.volume | 54 | cs |
| dc.description.firstpage | art. no. UNSP 100649 | cs |
| dc.identifier.wos | 000528484400009 | |