FACULTY OF ENGINEERING
Department of Software Engineering
SOCIAL MEDIA
IE 353 | Course Introduction and Application Information
| Course Name |
Optimization III
|
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
|
IE 353
|
Fall/Spring
|
2
|
2
|
3
|
8
|
| Prerequisites |
|
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| Course Language |
English
|
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| Course Type |
Service Course
|
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| Course Level |
First Cycle
|
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| Mode of Delivery | - | |||||||||||
| Teaching Methods and Techniques of the Course | - | |||||||||||
| Course Coordinator | ||||||||||||
| Course Lecturer(s) | ||||||||||||
| Assistant(s) | ||||||||||||
| Course Objectives | Most systems and processes of organizations operating in almost all kinds of sectors (private/public, service/manufacturing etc.) are stochastic in nature. The objective of this course is to give the students the analytical skills and knowledge related to stochastic processes and models necessary to improve the systems and processes used in varying organizations. |
| Learning Outcomes |
The students who succeeded in this course;
|
| Course Description | The main subjects of the course are the stochastic processes and their special kind called Markov chains, queueing theory, inventory theory and also possible real life applications. |
|
|
Core Courses | |
| Major Area Courses | ||
| Supportive Courses | ||
| Media and Management Skills Courses | ||
| Transferable Skill Courses |
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
| Week | Subjects | Related Preparation |
| 1 | Review of probability | Ross, Ch. 1 |
| 2 | Conditional Probability and Random Variables | Ross, Ch. 2 |
| 3 | Discrete, Continuous Random Variables and Expected Values | Ross, Ch. 3 |
| 4 | Stochastic Processes and Markov Chains | Winston, Ch. 17, Hillier & Lieberman Ch. 16 |
| 5 | Markov Chains | Winston, Ch. 17, Hillier & Lieberman Ch. 16 |
| 6 | Markov Chains | Winston, Ch. 17, Hillier & Lieberman Ch. 16 |
| 7 | Markov Chains | Winston, Ch. 17, Hillier & Lieberman Ch. 16 |
| 8 | Markov Decision Processes | Winston, Ch. 19.5, Hillier & Lieberman Ch. 19 |
| 9 | Continuous Time Markov Chains | Ross, Ch. 6, Hillier & Lieberman Ch. 16.8 |
| 10 | Queueing Theory: Terminology, Basic Structure | Winston, Ch. 20, Hillier & Lieberman Ch. 17 |
| 11 | Queueing Theory: Role of Exponential Distribution, Birth-Death Process | Winston, Ch. 20, Hillier & Lieberman Ch. 17 |
| 12 | Queueing Models | Winston, Ch. 20, Hillier & Lieberman Ch. 17 |
| 13 | Queueing Models | Winston, Ch. 20, Hillier & Lieberman Ch. 17 |
| 14 | Queueing Models | Winston, Ch. 20, Hillier & Lieberman Ch. 17 |
| 15 | Review of the semester | |
| 16 | Final Exam |
| Course Notes/Textbooks | [1] Sheldon Ross, Introduction to Probability Models, 12th edition, Academic Press, 2019.ISBN: 978-0-12-814346-9. [2] Wayne L. Winston, Operations Research: Applications and Algorithms, (International Student Edition), 4th Edition, Brooks/Cole, 2004. ISBN: 0-534-42362-0 [3] Frederick S. Hillier, Gerald J. Lieberman, Introduction to Operations Research, 10th Edition, 2010 Mc GrawHill, ISBN: 9780071267670 |
| Suggested Readings/Materials | [4] Sheldon Ross. A First Course in Probability. Fifth Ed., Prentice Hall, Ltd., 1997. [5] D. C. Montgomery and G. C. Runger. Applied Statistics and Probability for Engineers. 3th Edition, John Wiley & Sons, Inc., 2003. [6] Hwei Hu. Probability, Random Variables, and Random Processes. 2nd Edition, Schaum's Outlines, McGraw-Hill, 2010. |
EVALUATION SYSTEM
| Semester Activities | Number | Weigthing |
| Participation | ||
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques |
4
|
40
|
| Portfolio | ||
| Homework / Assignments | ||
| Presentation / Jury | ||
| Project |
1
|
20
|
| Seminar / Workshop | ||
| Oral Exams | ||
| Midterm | ||
| Final Exam |
1
|
40
|
| Total |
| Weighting of Semester Activities on the Final Grade |
2
|
60
|
| Weighting of End-of-Semester Activities on the Final Grade |
1
|
40
|
| Total |
ECTS / WORKLOAD TABLE
| Semester Activities | Number | Duration (Hours) | Workload |
|---|---|---|---|
| Theoretical Course Hours (Including exam week: 16 x total hours) |
16
|
2
|
32
|
| Laboratory / Application Hours (Including exam week: '.16.' x total hours) |
16
|
2
|
32
|
| Study Hours Out of Class |
14
|
5
|
70
|
| Field Work |
0
|
||
| Quizzes / Studio Critiques |
4
|
12
|
48
|
| Portfolio |
0
|
||
| Homework / Assignments |
0
|
||
| Presentation / Jury |
0
|
||
| Project |
1
|
22
|
22
|
| Seminar / Workshop |
0
|
||
| Oral Exam |
0
|
||
| Midterms |
0
|
||
| Final Exam |
1
|
36
|
36
|
| Total |
240
|
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
|
#
|
Program Competencies/Outcomes |
* Contribution Level
|
||||
|
1
|
2
|
3
|
4
|
5
|
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| 1 | To have adequate knowledge in Mathematics, Science, Computer Science and Software Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems. |
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| 2 | To be able to identify, define, formulate, and solve complex Software Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose. |
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| 3 | To be able to design, implement, verify, validate, document, measure and maintain a complex software system, process, or product under realistic constraints and conditions, in such a way as to meet the requirements; ability to apply modern methods for this purpose. |
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| 4 | To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in software engineering applications; to be able to use information technologies effectively. |
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| 5 | To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex Software Engineering problems. |
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| 6 | To be able to work effectively in Software Engineering disciplinary and multi-disciplinary teams; to be able to work individually. |
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| 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 be able to present effectively, to be able to give and receive clear and comprehensible instructions. |
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| 8 | To have knowledge about global and social impact of engineering practices and software applications on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Engineering and Software Engineering solutions. |
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| 9 | To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications. |
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| 10 | To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development. |
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| 11 | To be able to collect data in the area of Software Engineering, and to be able to communicate with colleagues in a foreign language. ("European Language Portfolio Global Scale", Level B1) |
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| 12 | To be able to speak a second foreign language at a medium level of fluency efficiently. |
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| 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 Software Engineering. |
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*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
SOCIAL MEDIA