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New Applications for Logic planning of traditional and agile projects. Judit Kiss PhD candidate. Content of the presentation. Matlab applications. genetic algorithm based on GAlib. Project management approaches *. Software development, product development projects.
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New ApplicationsforLogicplanning of traditional and agileprojects Judit Kiss PhD candidate
Content of thepresentation Matlabapplications genetic algorithm based on GAlib
Project management approaches* Software development, productdevelopmentprojects Constructionprojects 20% 70% 10% R&D projects * Wysocki, Robert K.: Effective Project Management: Traditional, Agile, Extreme, Wiley Publishing, Inc., Indianapolis, Indiana, 5th ed., 2009, ISBN 978-0-470-42367-7.
Traditional vs. agile project planning Traditional project planning Agile project planning Fixed Scope Time Budget Variable Scope Budget Time (Dalcher, 2009, PMUni)
Specialities of IT projects • Atlogicplanning prior experiencecan be reused • Stochastictaskswithstochasticdurations • More possible project scenarios • Realizingtaskscan be rankedbytheirimportance • Less importanttasks/functionscan be left out fromthe project • Stochastic relations betweentasks • More possible project structures • Taskscan be repeatedortasksequencescanbereversed • Flexibleorder of tasksequences, • Severaltaskscan be realizedparallelly and alsosequentially
Matrix-based project planningmethods SNPM - Relations betweentaskscan be: 0: independent/parallel relation 0-1: uncertain/possiblerelation 1: certain/sequentialrelation PEM - Uncertainty of taskcan be: 0: taskcan be omitted 0-1: uncertaintask 1: certaintask • DSM * • SNPM ** • PEM *** *** Project Expert Matrix (J. Kiss – Zs. Kosztyán, 2009, Confenis, AVA) * DependencyStructureMatrix (Steward, 1981; dsmweb.org) ** Stochastic Network PlanningMethod (Zs.Kosztyán-J.Fejes-J.Kiss, 2008, Szigma)
Project scenarios - Selectingthetasks Step 1 Budget … Selectedtasks: A, C, E, B, D
Project structures – different relations Step 2 CriticalPathMethod PrecedenceDiagrammingMethod Generatingallpossible project structuresbasedonthematrixvalues GraphicalEvaluation and ReviewTechnique ExtendedEvent-drivenProcessChain …
Selectingtheoptimalsolution Reorderingthetasks
Project scenario and structureGenerating&RankingAlgorithm Step 1 Step 2 MatlabapplicationbyJ.Kiss, basedon PSSM algorithm(Kosztyán – Kiss, 2010, DSM) Fullevaluatingalgorithm
AgileProjectPlanning Algorithm Step 1 Step 2 What? Whichtasks? How? Inwhichorder? Howlong? Howmuch? Matlabapplicationby J. Kiss, basedonthe APS algorithm(Kosztyán-Kiss, 2010, Vezetéstudomány)
Matrix-based Project Planning Genetic Algorithm Population Selection Population of thenewgeneration Crossover, mutation Selection GA applicationby I. Borbás
Genetic operators– Crossover #1 Genetic algorithm
Mutation Selection Geneticoperators • Negatingoneor more elements • TournamentSelector
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Novelty of my research • PEM matrix • Supportingthelogicplanningbyhandlingthepossibletaskoccurrances and possible relations • The possiblesolutionscan be generated and ranked • Logicplanscan be restructured • Applyablefortraditional and agileprojects • Matrix-basedapplicationsareuseful and applicableat PEM matrixwithhigheruncertaintyaswell. • APPAgivestheoptimalsolutionbasedonthevaluesinthe PEM. • MPPGA is practicaltoget a goodsolutiontakingdifferentconstraints and multipleobjectivefunctioninto account.
Thankyouforyourkindattention. kissjudit@gtk.uni-pannon.hu