Numerical Analysis of The Differential Evolution Optimization Algorithm and Its Control  Parameters

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Title:	Numerical Analysis of The Differential Evolution Optimization Algorithm and Its Control Parameters
Authors:	BABAUOSMAIL, Idris Hadj Daoud, ABDERRAHMAN
Keywords:	Global Optimization, Meta-heuristic Algorithms (GA, ABC, PSO), Differential Evolution (DE), Control Parameters, DE Variants, Benchmark Functions, Convergence Quality, Convergence Speed, Execution Time.
Issue Date:	2024
Publisher:	Blida1
Abstract:	This thesis aims to investigate the impact of control parameters and variants of the DE algorithm on its performance. By analyzing parameters like population size and mutation rates, alongside exploring various DE algorithm variants, the study aims to understand their combined influence on algorithm efficiency. Moreover, this research has the potential to be applied to various fields requiring optimization, including Maximum Power Point Tracking (MPPT).
Description:	4.333.1.366 ; 109 p
URI:	https://di.univ-blida.dz/jspui/handle/123456789/40289
Appears in Collections:	Mémoires de Master

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Final_THESIS.pdf		2,71 MB	Adobe PDF	View/Open

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