Improved Gravitational Search Algorithm for Solving Optimization Problems / Rayene Assil

Public ISBD Titre : Improved Gravitational Search Algorithm for Solving Optimization Problems Type de document : texte imprimé Auteurs : Rayene Assil, Auteur ; Fatma Zohra Kemouche ; Ihcene Naas, Directeur de thèse Editeur : Sétif:UFS Année de publication : 2024 Importance : 1 vol (25 f.) Format : 29 cm Langues : Anglais (eng) Catégories : Thèses & Mémoires:Mathématique Mots-clés : Optimizationproblem Metaheuristic GravitationalSearchAlgorithm Stochasticstability  PlanetaryGearTrainproblem Index. décimale : 510-Mathématique Résumé : Inaddressingreal-worldoptimizationchallenges,classicaloptimizationmethodsoftenfallshort,leading to theriseofmetaheuristicalgorithms.Analyzingthestabilityofthesealgorithmsisessentialforun- derstandingtheirfunctionality,definingstabilitydomainsforcontrolparameters,andenhancingtheir efficacy.ThisstudyfocusesonmodelingandstabilityanalysisoftheGravitationalSearchAlgorithm(GSA), a prominentmetaheuristicinspiredbygravitationalinteractions.Mimickingcelestialbodies’movements, GSA collaborativelyexploressolutionspacestotacklecomplexoptimizationtasks.ThroughtheVan Neumancriteria,thealgorithm’sstochasticstabilityconditionsarederivedandutilizedtorefineparame- terization.AsimulationisconductedonthePlanetaryGearTrainproblemtovalidatethetheoreticalfindings. Note de contenu : Sommaire 1 Metaheuristics:Generalitiesanddefinitions1 1.1Introduction........................................ 1 1.2Preliminaries....................................... 1 1.2.1Optimizationproblem.............................. 1 1.2.2Combinatorialoptimization.......................... 2 1.2.3Complexity.................................... 3 1.2.4Optimizationmethods.............................. 4 1.3Metaheuristics....................................... 5 1.3.1Overviewofmetaheuristicalgorithms..................... 5 1.3.2Texonomyofmeta-heuristicalgorithms................... 6 1.3.3Stabilityofmetaheuristicalgorithms..................... 7 2 GravitationalSearchAlgorithm:Overviewandstabilityanalysis9 2.1Introduction........................................ 9 2.2Overviewongravitationalsearchalgorithm..................... 9 2.2.1Thepseudo-codeofGSAalgorithm...................... 12 2.3Stabilityanalysis..................................... 12 2.3.1Relatedwork.................................... 12 2.3.2VanNeumanstability.............................. 14 2.3.3Model........................................ 14 3 ApplicationofGSAfornoisereductioninplanetarygearstrain18 3.1Introduction........................................ 18 3.2PlanetaryGearTrainproblem.............................. 18 3.2.1Theformulationoftheproblem........................ 19 3.3Experimentalresultsandanalysis........................... 22 3.3.1Testedalgorithms................................. 22 3.3.2Parametersettings................................ 22 3.3.3Constrainthandling............................... 23 3.3.4Resultsanddiscussions............................. 23 Côte titre : MAM/0730 Improved Gravitational Search Algorithm for Solving Optimization Problems [texte imprimé] / Rayene Assil, Auteur ; Fatma Zohra Kemouche ; Ihcene Naas, Directeur de thèse . - [S.l.] : Sétif:UFS, 2024 . - 1 vol (25 f.) ; 29 cm. Langues : Anglais (eng) Catégories : Thèses & Mémoires:Mathématique Mots-clés : Optimizationproblem Metaheuristic GravitationalSearchAlgorithm Stochasticstability  PlanetaryGearTrainproblem Index. décimale : 510-Mathématique Résumé : Inaddressingreal-worldoptimizationchallenges,classicaloptimizationmethodsoftenfallshort,leading to theriseofmetaheuristicalgorithms.Analyzingthestabilityofthesealgorithmsisessentialforun- derstandingtheirfunctionality,definingstabilitydomainsforcontrolparameters,andenhancingtheir efficacy.ThisstudyfocusesonmodelingandstabilityanalysisoftheGravitationalSearchAlgorithm(GSA), a prominentmetaheuristicinspiredbygravitationalinteractions.Mimickingcelestialbodies’movements, GSA collaborativelyexploressolutionspacestotacklecomplexoptimizationtasks.ThroughtheVan Neumancriteria,thealgorithm’sstochasticstabilityconditionsarederivedandutilizedtorefineparame- terization.AsimulationisconductedonthePlanetaryGearTrainproblemtovalidatethetheoreticalfindings. Note de contenu : Sommaire 1 Metaheuristics:Generalitiesanddefinitions1 1.1Introduction........................................ 1 1.2Preliminaries....................................... 1 1.2.1Optimizationproblem.............................. 1 1.2.2Combinatorialoptimization.......................... 2 1.2.3Complexity.................................... 3 1.2.4Optimizationmethods.............................. 4 1.3Metaheuristics....................................... 5 1.3.1Overviewofmetaheuristicalgorithms..................... 5 1.3.2Texonomyofmeta-heuristicalgorithms................... 6 1.3.3Stabilityofmetaheuristicalgorithms..................... 7 2 GravitationalSearchAlgorithm:Overviewandstabilityanalysis9 2.1Introduction........................................ 9 2.2Overviewongravitationalsearchalgorithm..................... 9 2.2.1Thepseudo-codeofGSAalgorithm...................... 12 2.3Stabilityanalysis..................................... 12 2.3.1Relatedwork.................................... 12 2.3.2VanNeumanstability.............................. 14 2.3.3Model........................................ 14 3 ApplicationofGSAfornoisereductioninplanetarygearstrain18 3.1Introduction........................................ 18 3.2PlanetaryGearTrainproblem.............................. 18 3.2.1Theformulationoftheproblem........................ 19 3.3Experimentalresultsandanalysis........................... 22 3.3.1Testedalgorithms................................. 22 3.3.2Parametersettings................................ 22 3.3.3Constrainthandling............................... 23 3.3.4Resultsanddiscussions............................. 23 Côte titre : MAM/0730

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