Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/24537
Title: Design optimization of power objects based on Constrained non-linear minimization, Genetic algorithms, Particle swarm optimization algorithms and Differential Evolution Algorithms
Authors: Salkoski, Rasim
Chorbev, Ivan
Keywords: Constrained non-linear minimization, Genetic Algorithms, Particle Swarm Optimization, Differential Evolution, Arc Suppression Coil
Issue Date: 1-Sep-2014
Journal: International Journal on Information Technologies and Security
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.
URI: http://hdl.handle.net/20.500.12188/24537
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles

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