Runtime analysis of discrete particle swarm optimization algorithms: A survey
| dc.contributor.author | Mühlenthaler, Moritz | |
| dc.contributor.author | Raß, Alexander | |
| dc.date.accessioned | 2021-06-21T12:16:42Z | |
| dc.date.available | 2021-06-21T12:16:42Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | A discrete particle swarm optimization (PSO) algorithm is a randomized search heuristic for discrete optimization problems. A fundamental question about randomized search heuristics is how long it takes, in expectation, until an optimal solution is found. We give an overview of recent developments related to this question for discrete PSO algorithms. In particular, we give a comparison of known upper and lower bounds of expected runtimes and briefly discuss the techniques used to obtain these bounds. | en |
| dc.identifier.doi | 10.1515/itit-2019-0009 | |
| dc.identifier.pissn | 2196-7032 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/36657 | |
| dc.language.iso | en | |
| dc.publisher | De Gruyter | |
| dc.relation.ispartof | it - Information Technology: Vol. 61, No. 4 | |
| dc.subject | randomized search heuristics | |
| dc.subject | particle swarm optimization | |
| dc.subject | runtime analysis | |
| dc.title | Runtime analysis of discrete particle swarm optimization algorithms: A survey | en |
| dc.type | Text/Journal Article | |
| gi.citation.endPage | 185 | |
| gi.citation.publisherPlace | Berlin | |
| gi.citation.startPage | 177 |