Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/24537| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Salkoski, Rasim | en_US |
| dc.contributor.author | Chorbev, Ivan | en_US |
| dc.date.accessioned | 2022-11-23T09:27:33Z | - |
| dc.date.available | 2022-11-23T09:27:33Z | - |
| dc.date.issued | 2014-09-01 | - |
| dc.identifier.uri | http://hdl.handle.net/20.500.12188/24537 | - |
| dc.description.abstract | This paper gives a detailed comparative analysis of Constrained non-linear minimization (CN), Genetic Algorithms (GA), Particle Swarm Optimization Algorithms (PSO) and Differential Evolution Algorithms (DE) results. The Objective Function that is optimized is a minimization dependent and all constraints are normalized and modeled as inequalities. The results demonstrate the potential of the DE Algorithm, shows its effectiveness and robustness to solve the optimal power object. | en_US |
| dc.relation.ispartof | International Journal on Information Technologies and Security | en_US |
| dc.subject | Constrained non-linear minimization, Genetic Algorithms, Particle Swarm Optimization, Differential Evolution, Arc Suppression Coil | en_US |
| dc.title | Design optimization of power objects based on Constrained non-linear minimization, Genetic algorithms, Particle swarm optimization algorithms and Differential Evolution Algorithms | en_US |
| dc.type | Journal Article | en_US |
| item.grantfulltext | open | - |
| item.fulltext | With Fulltext | - |
| Appears in Collections: | Faculty of Computer Science and Engineering: Journal Articles | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2014_N3-03.pdf | 449.46 kB | Adobe PDF | View/Open |
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