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 Cursus: 202000425
 202000425Stochastic Models
 Cursus informatie
Cursus202000425
Studiepunten (ECTS)5
CursustypeOnderwijseenheid
VoertaalEngels
Contactpersoondr.ir. L.L.M. van der Wegen
E-maill.l.m.vanderwegen@utwente.nl
Docenten
 Vorige 1-5 van 106-10 van 10 Volgende 5
 Examinator dr. A. Asadi Docent dr.ir. A. Braaksma Docent dr. S.M. Meisel Docent dr. S. Rachuba Docent dr.ir. W.R.W. Scheinhardt
Collegejaar2022
Aanvangsblok
 2B
AanmeldingsprocedureZelf aanmelden via OSIRIS Student
Inschrijven via OSIRISJa
 Cursusdoelen
 body { font-size: 9pt; font-family: Arial } table { font-size: 9pt; font-family: Arial } After successful completion of this module component, the student is able to: formulate a Markov chain model for a given problem description and solve this model; formulate a Stochastic Dynamic Programming (SDP) model for a given problem description and solve this model; formulate a Markov Decision Process (MDP) model for a given problem description and solve this model; interpret the outcomes of an SDP and MDP model in order to construct an optimal strategy, which is applicable in a given practical situation; select an appropriate queueing model (M/M/1, M/M/c, etc.) for a given problem description and solve this model; interpret the implications of a queueing systemâ€™s performance on (given) performance indicators and formulate practical recommendations for system improvement.
 Inhoud
 body { font-size: 9pt; font-family: Arial } table { font-size: 9pt; font-family: Arial } Students first learn the basics of Markov chains (in discrete and continuous time, and Poisson processes). Using that knowledge, they next learn about stochastic dynamic programming and about queueing theory. Stochastic dynamic programming can be used to solve sequential multistage decision problems under uncertainty, e.g., transportation planning for multiple time periods with uncertain order arrivals and transportation times. Queueing theory can be used to analyse queueing problems that occur, e.g., in production and logistics, service industries, and communication networks.
 Assessment
 body { font-size: 9pt; font-family: Arial } table { font-size: 9pt; font-family: Arial } Passing grade is 5.5 (average of two subtests on SDP and Queueing) and a score of at least 40% on all subtests (SDP and Queueing). In case of passing one of the subtests (SDP or Queuing) the score remains valid for the same year. But, in case of failing the Stochastic models, both parts needs redo for the upcoming year. Max of Exam 1 and Exam 2 counts.
Voorkennis
 1. Probability theory (e.g., random variables, cumulative distribution functions, probability density functions, conditional distributions and measures of a distribution).2. Operations research (e.g., basic knowledge of queueing models and understands the idea behind dynamic programming).
 Participating study
 Bachelor Technische Bedrijfskunde
 Module
 Module 8
Verplicht materiaal
Book
 WL Winston – Operations Research: Applications and Algorithms, 4th edition ISBN: 9780357337769 (ebook)
Aanbevolen materiaal
-
Werkvormen
 Hoorcollege Vragenuur Werkcollege Zelfstudie geen begeleiding
Toetsen
 Stochastic Models Exam
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