Introduction to Simulation; Review of Simulation Models; Statistical Models for Simulation; Queueing Models; Inventory Systems; Random Numbers; Input Data Analysis; Output Analysis; Verification & Validation of Simulation Models; Evaluation of Alternative System Designs; Simulation of Manufacturing Systems.
Prerequisite(s)
-
Corequisite(s)
-
Special Requisite(s)
-
Instructor(s)
Course Assistant(s)
-
Schedule
The course is not opened for this semester.
Office Hour(s)
The course is not opened for this semester.
Teaching Methods and Techniques
Term/Report/Project: Students will be assigned in teams of three to work on term projects. Three progress and one final reports are mandatory.
Laboratuary Work: Lab applications are done at the computer lab using desktop computers. Statistical analysis is performed. ARENA, a simulation package, will be covered and used for simulating systems.
Principle Sources
1. Banks, J., Carson II, J.S. and Nelson, B.L. (2009). Discrete-Event System Simulation (5th ed.). Prentice Hall. 0136062121.
2. Kelton, W.D., Sadowski, R.P., and Sturrock, D.T. (2010). Simulation with Arena (5th ed.). McGraw-Hill. 0072919817.
Other Sources
1. Law, A.M. and Kelton, W.D. (2000). Simulation Modeling and Analysis (3rd ed.). McGraw-Hill. 0070592926.
Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction. Types of Simulation. Static simulation examples
Oral Presentation, Laboratory
2. Week
Advantages and disadvantages of simulation. Steps in simulation. Dynamic simulation examples.
Oral Presentation, Laboratory
3. Week
Components of discrete event simulation. Collection of statistics. Hand simulation
Oral Presentation, Laboratory
4. Week
Probability review.
Oral Presentation, Laboratory
5. Week
Simulation of a Single-Server Queueing System.
Oral Presentation, Laboratory, Project
6. Week
Random Number Generators Generators Used by Simulation Languages.
Oral Presentation, Laboratory
7. Week
Tests for Random Numbers. Frequency for tests. Tests for autocorrelation.
Oral Presentation, Laboratory
8. Week
Generating Random Variates. Inverse-Transform Technique. Acceptance-Rejection Technique. Special Properties.
Oral Presentation, Laboratory
9. Week
Input Distribution Fitting: Histogram, PP, and QQ chart.
Oral Presentation, Laboratory
10. Week
Input Distribution Fitting: Goodness of fit tests: Chi-square test, KS test.
Output Analysis: Comparison and Evaluation of Alternative System Designs.
Oral Presentation, Laboratory
15. Week
Variance Reduction Techniques: Indirect measures, control variants.
Oral Presentation, Laboratory
16. Week
Variance Reduction Techniques: Common random numbers, antithetic random numbers.
Oral Presentation, Laboratory
17. Week
Simulation of Manufacturing and Material-Handling Systems.
Project presentation
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
20
Quizzes
3
15
Homework / Term Projects / Presentations
1
15
Project(s)
1
10
Attendance
1
0
Final Exam
1
40
Program Outcomes
PO-1
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.
PO-2
Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose.
PO-3
Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.)
PO-4
Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
PO-5
Ability to design and conduct experiments, gather data, analyse and interpret results for investigating engineering problems.
PO-6
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
PO-7
Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language.
PO-8
Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
PO-9
Awareness of professional and ethical responsibility.
PO-10
Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
PO-11
Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.
Learning Outcomes
LO-1
Design a system, component, or process to meet the requirements within realistic constraints.
LO-2
Develop a simulation model of a system and simulate the system by hand.
LO-3
Generate random variates using random numbers for a given probability distribution.
LO-4
Apply runs tests, sketch histogram, PP and QQ graphs, practice Chi-Square and Kolmogorov-Smirnov tests.
LO-5
Develop, run, verify, and validate a simulation model using ARENA
LO-6
Design and conduct experiments, as well as to analyze and interpret data.
LO-7
Determine model features, terminating, or non terminating models, number of runs, calculate confidence interval and interpret the results.
LO-8
Perform variance reduction techniques; indirect measure, control variants, common random variants, antithetic variants.
