| Titre : | Intelligent University Pedagogical Management and Scheduling Platform |
| Auteurs : | Athmane Soumia, Auteur ; Saker Nada, Auteur ; Soumia Mebarki, Auteur ; Bilal Mokhtari, Directeur de thèse |
| Editeur : | Biskra [Algérie] : Faculté des Sciences Exactes et des Sciences de la Nature et de la Vie, Université Mohamed Khider, 2024 |
| Format : | 1 vol. (77 p.) / ill., couv. ill. en coul / 30cm |
| Langues: | Français |
| Résumé : |
La planificationdesactivit´es universitairestellesquelescours,lesexamens,laplani- fication desremplacementsetlesprojetsdefind’´etudes estunetˆache difficileettr`eschronophage. Leprincipald´efi provientdelan´ecessit´e deprogrammerdiff´erents typesde sessions(cours,travauxdiri ´es, travauxpratiquesetexamens) `a traversdif erentsniveauxd’´etudes,entenantcomptedescontraintestellesqueladisponibilit´e dessallesde classeetdesenseignants,ainsiquedesexigencessp´ecifiques dechaquecours.Dansceprojet,nousintroduisonsunenouvelleapplicationmultiplateforme(webetmobile)qui esttr`es b´en´efique pourlepersonneladministratif,les ´etudiants etlesenseignants,car ellefacilitelacommunicationetam´eliore laplanificationdediversestˆaches. Lapro-grammation desactivit´es p´edagogiques tellesquelescours,lesexamensetl’attribution de projetsdefind’´etudes estenti`erement automatis´ee `a l’aided’unalgorithme´en´etiquemulti-objectifs. Ainsi,l’applicationr´eduit consid´erablementl’effortmanuelrequisetam´eliore lasatisfactionglobalevis-`a-vis desexigencesdeplanification,cequienfait un outilpr´ecieux pourlesinstitutions ´educatives |
| Sommaire : |
General Introductionxv Chapter 1:Schedulingproblem 1.1 Introduction................................3 1.2 Schedule..................................3 1.3 Schedulingasaproblem.........................4 1.4 Schedulingtechniques..........................5 1.4.1 Manualtechniques........................5 1.4.1.1 Nonevisualmethods.................5 1.4.1.2 Visualtechniques...................6 1.4.2 Automatedtechniques......................6 1.4.2.1 Mathematicaloptimizationtechniques........7 1.4.2.2 Heuristicstechniques.................10 1.4.2.3 MachineLearningbasedtechniques.........16 1.4.2.4 DeepLearningTechniques..............19 1.4.2.5 Rule-Basedtechniques(ExpertSystems).......23 1.5 Conclusion................................24 Chapter 2:GeneticAlgorithm:AcademicSchedulingOptimization 2.1 Introduction................................27 2.2 Evolutionaryalgorithms(EAs)......................27 2.3 GeneticAlgorithms(GA).........................28 2.4 ComponentsandprocessesofGeneticAlgorithms............28 2.4.1 BasicconceptsofGA.......................28 2.4.1.1 Genes.........................28 2.4.1.2 Chromosomes.....................29 2.4.1.3 Population.......................29 2.4.2 PhasesofGeneticAlgorithms..................30 2.4.2.1 Initialization......................30 2.4.2.2 Selection........................32 2.4.2.3 Crossover.......................33 2.4.2.4 Mutation........................35 2.4.2.5 Evaluation.......................37 2.4.2.6 Generation.......................38 2.4.3 Convergenceingeneticalgorithms...............38 2.5 Geneticalgorithmsclasses........................39 2.5.1 Single-ObjectiveGeneticAlgorithms(SGA)..........40 2.5.1.1 ElitistAlgorithms:...................40 2.5.1.2 Non-ElitistAlgorithms................40 2.5.2 Multi-ObjectiveGeneticAlgorithms(MOGA).........42 2.5.2.1 ElitistAlgorithms...................42 2.5.2.2 Non-ElitistAlgorithms................44 2.6 ApplicationofGeneticAlgorithmsinscheduling............45 2.6.1 Problemrepresentation......................45 2.6.1.1 Representationofcourses...............45 2.6.1.2 Geneticrepresentationforcourses..........46 2.6.1.3 Representationofexams................49 2.6.1.4 Geneticrepresentationforexams...........50 2.6.2 SchedulingwithNSGA-II:Fromtheorytopractice.......52 2.6.2.1 RationaleforChoosingNSGA-II...........52 2.6.2.2 ApplicationofNSGA-IIfortheschedulingsystem..52 2.7 Conclusion................................62 Chapter 3:AnalysisandConception 3.1 Introduction................................65 3.2 UnifiedModelingLanguagedefinition..................65 3.2.1 Usecasediagram.........................65 3.2.2 ClassDiagram..........................66 3.2.3 SequenceDiagram........................66 3.3 Systemdesign...............................67 3.3.1 Professorspart..........................67 3.3.1.1 Professorsfunctionalities...............67 3.3.1.2 Professorsusecasediagram..............67 3.3.2 Administratorrole........................69 3.3.2.1 Administratorfunctionalities.............69 3.3.2.2 Administratorusecasediagram............70 3.3.3 Studentrole............................72 3.3.3.1 Studentfunctionalities.................72 3.3.3.2 Studentusecasediagram...............72 3.3.4 Detailedspecification.......................73 3.3.4.1 Classdiagrams.....................73 3.3.4.2 Sequencediagram...................79 3.4 Conclusion................................81 Chapter 4:Implementationanddeployment 4.1 Introduction................................83 4.2 Developmenttoolsandtechnologies...................83 4.2.1 Back-endtools..........................83 4.2.2 Front-endtools..........................85 4.3 SystemArchitecture............................87 4.4 Implementation:Featuresandfunctionalities..............91 4.4.1 WebApplication.........................91 4.4.2 Mobileapplication........................130 4.5 Resultsofthegeneticalgorithmscheduling...............140 4.5.1 Geneticalgorithmconfiguration.................141 4.5.2 Obtainedresults.........................142 4.5.2.1 Courses schedulingalgorithm . .............142 4.5.2.2 Examsplanningalgorithm...............146 4.6 Conclusion................................149 4.7 Futureenhancements...........................149 |
| Type de document : | Mémoire master |
Disponibilité (1)
| Cote | Support | Localisation | Statut |
|---|---|---|---|
| MINF/873 | Mémoire master | bibliothèque sciences exactes | Consultable |
