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

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DC Field	Value	Language
dc.contributor.author	BABAUOSMAIL, Idris	-
dc.contributor.author	Hadj Daoud, ABDERRAHMAN	-
dc.date.accessioned	2025-07-16T10:08:30Z	-
dc.date.available	2025-07-16T10:08:30Z	-
dc.date.issued	2024	-
dc.identifier.uri	https://di.univ-blida.dz/jspui/handle/123456789/40289	-
dc.description	4.333.1.366 ; 109 p	fr_FR
dc.description.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).	fr_FR
dc.language.iso	en	fr_FR
dc.publisher	Blida1	fr_FR
dc.subject	Global Optimization, Meta-heuristic Algorithms (GA, ABC, PSO), Differential Evolution (DE), Control Parameters, DE Variants, Benchmark Functions, Convergence Quality, Convergence Speed, Execution Time.	fr_FR
dc.title	Numerical Analysis of The Differential Evolution Optimization Algorithm and Its Control Parameters	fr_FR
Appears in Collections:	Mémoires de Master

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