FACULTY OF ENGINEERING

Department of Industrial Engineering

IE 339 | Course Introduction and Application Information

Course Name
Queueing Systems
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
IE 339
Fall/Spring
3
0
3
6

Prerequisites
  IE 353 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Service Course
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course -
Course Coordinator -
Course Lecturer(s) -
Assistant(s) -
Course Objectives The purpose of this course is to introduce students to a general framework for modeling queueing systems and to the basic methodologies used for their analysis.
Learning Outcomes The students who succeeded in this course;
  • Will be able to explain the framework for modelling and analyzing queueing systems
  • Will be able to define the stochastic processes that are used in the analyses of queueing systems
  • Will be able to explain the available analytical models for queueing systems
  • Will be able to relate a system under consideration with known queueuing models
  • Will be able to use queueing models for performance analysis of service and production systems
Course Description The purpose of this course is to introduce students to a general framework for modeling queueing systems and to the basic methodologies used for their analysis. Since queueing phenomenon is in general due to randomness, the course requires extensive use of probability theory. The course will encompass the stochastic processes necessary for analyzing queueing systems. At the end the course, the students are supposed to be acquainted with the available analytical models for queueing systems and to be able to use them for performance analysis of service and production systems.

 



Course Category

Core Courses
Major Area Courses
X
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Characteristics of Queueing Systems Ch 1 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
2 Performance Evaluation Concepts Ch 1 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
3 Poisson Process and Exponential Distribution Ch 2 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
4 Markov Chains Ch 2 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
5 Simple Markovian BirthDeath Queueing Models Ch 3 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
6 Simple Markovian BirthDeath Queueing Models Ch 3 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
7 Review and Midterm Exam
8 Advanced Markovian Queueing Models Ch 4 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
9 Advanced Markovian Queueing Models Ch 4 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
10 Queueing Networks Ch 5 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
11 Queueing Networks Ch 5 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
12 General Distribution Models Ch 6 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
13 General Distribution Models Ch 6 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
14 Advanced Topics Ch 7 D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
15 General review and evaluation
16 Review of the Semester  

 

Course Notes/Textbooks D. Gross, CM. Harris, Queueing Theory, Wiley, 2009.
Suggested Readings/Materials

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
1
10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
3
10
Presentation / Jury
Project
1
20
Seminar / Workshop
Oral Exams
Midterm
1
30
Final Exam
1
30
Total

Weighting of Semester Activities on the Final Grade
70
Weighting of End-of-Semester Activities on the Final Grade
30
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
0
Study Hours Out of Class
15
4
60
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
3
7
21
Presentation / Jury
0
Project
1
20
20
Seminar / Workshop
0
Oral Exam
0
Midterms
1
8
8
Final Exam
1
13
13
    Total
170

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have adequate knowledge in Mathematics, Science and Industrial Engineering; to be able to use theoretical and applied information in these areas to model and solve Industrial Engineering problems.

X
2

To be able to identify, formulate and solve complex Industrial Engineering problems by using state-of-the-art methods, techniques and equipment; to be able to select and apply proper analysis and modeling methods for this purpose.

X
3

To be able to analyze a complex system, process, device or product, and to design with realistic limitations to meet the requirements using modern design techniques.

X
4

To be able to choose and use the required modern techniques and tools for Industrial Engineering applications; to be able to use information technologies efficiently.

X
5

To be able to design and do simulation and/or experiment, collect and analyze data and interpret the results for investigating Industrial Engineering problems and Industrial Engineering related research areas.

X
6

To be able to work efficiently in Industrial Engineering disciplinary and multidisciplinary teams; to be able to work individually.

X
7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively; to be able to give and receive clear and comprehensible instructions

8

To have knowledge about contemporary issues and the global and societal effects of Industrial Engineering practices on health, environment, and safety; to be aware of the legal consequences of Industrial Engineering solutions.

9

To be aware of professional and ethical responsibility; to have knowledge of the standards used in Industrial Engineering practice.

10

To have knowledge about business life practices such as project management, risk management, and change management; to be aware of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Industrial Engineering; to be able to communicate with colleagues in a foreign language.

12

To be able to speak a second foreign at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Industrial Engineering.

X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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