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  2. Technische Fakultät
  3. Department Informatik
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Simulation and Modeling 1 (WS 2019/20)

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Simulation and Modeling 1 (WS 2019/20)

Lecture

Prof. Dr.-Ing. Reinhard German

Head of Computer Science 7
  • Phone number: +49913185-27916
  • Email: reinhard.german@fau.de

Exercises

Lisa Maile, M. Sc.

  • Phone number: +49 9131 85-28700
  • Email: lisa.maile@fau.de

Dr.-Ing. Daniel Scharrer

  • Phone number: +49 9131 85-28025
  • Email: daniel.scharrer@fau.de

Due to the corona virus, all examinations temporarily are cancelled. We have no idea when the exam will take place instead. You will be informed via StudOn as soon as we have more information. We will also announce the new date on this website.

Details

Type of Course Lecture (2 SWS) + Exercise (2 SWS)
ECTS Credits 2,5 + 2,5
Language English
Lecture

Thursday, 14:15 – 15:45, Room KS I UnivIS

Exercises

Tuesday, 12:15 – 13:45, Room 04.158 UnivIS
Tuesday, 16:15 – 17:45, Room 04.158 UnivIS
Thursday, 8:15 – 9:45, Room 01.153-113 UnivIS

Registration for the Exercises via StudOn, starting October 17th at 8 pm
StudOn: 5.TECH -> 5.3 INF -> INF 7 -> Simulation and Modeling WS19/20

In case of any questions, contact simmod1@i7.informatik.uni-erlangen.de

Overview of the various kinds of simulation, discrete simulation (computational concepts, simulation of queuing systems, simulation in Java, professional simulation tools), required probability concepts and statistics, modeling paradigms (e.g., event/process-oriented, queuing systems, Petri nets, UML statecharts), input modeling (selecting input probability distributions), random number generation (linear congruential generators and variants, generating random variates), output analysis (warm-up period detection, independent replications, result presentation), continuous and hybrid simulation (differential equations, numerical solution, hybrid statecharts), simulation software, case studies, parallel and distributed simulation.

Calculation of expected values with the aid of probability theory, determination of confidence intervals, creation of simulation models using AnyLogic, hybrid modeling with statecharts, data collection and distribution fitting with ExpertFit.

The exercises will be held on Tuesday and Thursday and serve for practice of theory, usage of various tools, and for preparation of assignments. On selected days, these exercise hours will serve as programming hours, where an advisor will be present in order to assist in the current assignments.
When questions arise, the teaching assistant may be asked directly or be contacted in his office, via phone or via Email. Beyond the exercises, appointments for individual discussions may be arranged with the teaching assistant at any other time (also via Email). Otherwise, please limit your unappointed seek for individual assistance to the exercise or computer hours.

Law, Kelton: “Simulation Modeling and Analysis.” 5rd edition, McGraw Hill, 2014.

Exam Materials

  • Example Questions
  • Example Exam

Lecture Slides

  • Organization
  • Introduction
  • Discrete Simulation
  • Analytical Modeling
  • Modeling Paradigms
  • Input Modeling
  • Random Number Generators
  • Output Analysis
  • Continuous Simulation

Exercise Materials

  • Organization
  • Probability Theory
  • Real-Time UML and Anylogic
  • Java Introduction
  • Java Demonstration: Disco.alp
  • Petri Net Library
  • Statistics Tests
  • Random Variates

Exercises

  • Exercise 1
  • Exercise 2
  • Exercise 3
  • SimpleMM1Queue.alp
  • MG1QueueNoMeasures.alp
  • SMI_Ex3_3_SSJ_project.zip
  • ssj-master_3.2.0.zip
  • Exercise 4
  • PetriNetLibrary_8.1.jar
  • Holiday Project
  • Exercise5.zip
  • Exercise 6
  • CommNetwork_A5_MAP.alp
  • Exercise 7

Further Information

    Simulation and Modeling 1 (SaM 1) UnivIS
    Exercises to: Simulation and Modeling I (ESaM1) UnivIS
Computer Science 7 (Computer Networks and Communication Systems)
Friedrich-Alexander-Universität Erlangen-Nürnberg

Martensstr. 3
91058 Erlangen
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