MODELLING and SIMULATION

AIM

To make students understand the real job applications and provide solutions to the job improvement processes by making simulation of them on a computer environment.

CONTENT

This course contains; Introduction to Simulation,Input Analysis,Random-Number and Random-Variate Generation,Monte Carlo Simulation Examples,Dynamic Simulation Examples,Discrete-Event Simulation in Arena - Basic Operations Validation,Discrete-Event Simulation in Arena - Detailed Operations,Output Analysis - Terminating Simulations,Discrete-Event Simulation in Arena - Intermediate Modeling,Output Analysis - Steady State Simulations,Discrete-Event Simulation in Arena - Entity Transfer,Sample Applications I,Sample Applications II,Arena Process Analyzer.

1. 1

   1. Will be able to Make a hand simulation.

   Taught by: Problem Solving Method, Lecture Method · Assessed by: Traditional Written Exam, Homework

2. 2

   2. Will be able to apply Monte Carlo simulation.

   Taught by: Simulation Technique, Lecture Method · Assessed by: Traditional Written Exam, Homework

3. 3

   3. Use Linear Congrential Method to generate a random number

   Taught by: Problem Solving Method, Lecture Method · Assessed by: Traditional Written Exam, Homework

4. 4

   4. Will be able to make a discrete-event simulation using Arena.

   Taught by: Simulation Technique, Flipped Classroom Learning · Assessed by: Traditional Written Exam, Project Task

5. 5

   5. Will be able to analyze the outcomes of Arena.

   Taught by: Flipped Classroom Learning, Lecture Method · Assessed by: Traditional Written Exam, Project Task

WEEKLY PLAN

1. WEEK 1

   Introduction to Simulation

2. WEEK 2

   Input Analysis

3. WEEK 3

   Random-Number and Random-Variate Generation

4. WEEK 4

   Monte Carlo Simulation Examples

5. WEEK 5

   Dynamic Simulation Examples

6. WEEK 6

   Discrete-Event Simulation in Arena - Basic Operations Validation

7. WEEK 7

   Discrete-Event Simulation in Arena - Detailed Operations

8. WEEK 8

   Output Analysis - Terminating Simulations

9. WEEK 9

   Discrete-Event Simulation in Arena - Intermediate Modeling

10. WEEK 10

    Output Analysis - Steady State Simulations

11. WEEK 11

    Discrete-Event Simulation in Arena - Entity Transfer

12. WEEK 12

    Sample Applications I

13. WEEK 13

    Sample Applications II

14. WEEK 14

    Arena Process Analyzer

ASSESSMENT

• Rate of Midterm Exam to Success30%
• Rate of Final Exam to Success70%

WORKLOAD

READING

• J. Banks, J.S. Carson, B.L. Nelson and D.M. Nicol, Discrete-Event System Simulation, 3rd Edition, Prentice Hall, 2001 W.D. Kelton, R.P. Sadowski and D.A. Sadowski, Simulation with Arena, 2nd Edition, McGraw-Hill, 2002 3. S.H. Ross, Simulation, 2nd Edition, Academic Press,1997

TEACHING STAFF

• Assoc.Prof. Yasin GÖÇGÜNCOORDINATOR
• Assoc.Prof. Yasin GÖÇGÜN