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IE 590 | Course Introduction and Application Information
| Course Name |
Advanced Topics in IE and OR
|
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
|
IE 590
|
Fall/Spring
|
3
|
0
|
3
|
7.5
|
| Prerequisites |
None
|
|||||
| Course Language |
English
|
|||||
| Course Type |
Elective
|
|||||
| Course Level |
Second Cycle
|
|||||
| Mode of Delivery | - | |||||
| Teaching Methods and Techniques of the Course | - | |||||
| National Occupation Classification | - | |||||
| Course Coordinator | ||||||
| Course Lecturer(s) | ||||||
| Assistant(s) | - | |||||
| Course Objectives | The objective of this course is to determine the relative efficiencies of units (decision making units) in the production process or in any sector in the terms of their performance in converting inputs into outputs. The aims of the methodologies in this course are benchmarking, classification, ranking and making projection for these units. At this point, the methods both depent on time/not depent on time and deterministic/stochastic will be investigated. |
| Learning Outcomes |
The students who succeeded in this course;
|
| Course Description | Definition of efficiency and productivity terms, Introduction to Data Envelopment Analysis (DEA), Presentation of basic DEA models and their applications, Introduction to Stochastic Frontier Analysis (SFA), Presentation of basic SFA model and its applications, Introduction to Malmquist Index (MI), Presentation of MI method and its applications , Introduction to Window Analysis (WA), Presentation of WA method and its applications |
|
|
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 | Learning Outcome |
| 1 | Introduction to Modeling and Classification of Models | ||
| 2 | Modeling applications in GAMS and Pyomo | ||
| 3 | Modeling applications-Paper Selection for the first presentation | ||
| 4 | Modeling applications | ||
| 5 | Introduction to Power Systems | ||
| 6 | Mathematical models in power systems | ||
| 7 | Mathematical models in power systems | ||
| 8 | Presentations-First Paper Presentation | ||
| 9 | Mathematical models in power systems | ||
| 10 | Plant Location | ||
| 11 | National Holiday | ||
| 12 | Special Probelms | ||
| 13 | Presentations-Second Paper Presentation | ||
| 14 | Review of the term | ||
| 15 | Review of the term | ||
| 16 | Final Exam |
| Course Notes/Textbooks | Course notes |
| Suggested Readings/Materials | Instructor notes and lecture slides |
EVALUATION SYSTEM
| Semester Activities | Number | Weigthing |
| Participation | ||
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques |
2
|
20
|
| Portfolio | ||
| Homework / Assignments |
2
|
20
|
| Presentation / Jury |
1
|
20
|
| Project | ||
| Seminar / Workshop | ||
| Oral Exams | ||
| Midterm | ||
| Final Exam |
1
|
40
|
| Total |
| Weighting of Semester Activities on the Final Grade |
5
|
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
|
3
|
48
|
| Laboratory / Application Hours (Including exam week: '.16.' x total hours) |
16
|
0
|
|
| Study Hours Out of Class |
14
|
5
|
70
|
| Field Work |
0
|
||
| Quizzes / Studio Critiques |
2
|
13
|
26
|
| Portfolio |
0
|
||
| Homework / Assignments |
2
|
15
|
30
|
| Presentation / Jury |
1
|
21
|
21
|
| Project |
0
|
||
| Seminar / Workshop |
0
|
||
| Oral Exam |
0
|
||
| Midterms |
0
|
||
| Final Exam |
1
|
30
|
30
|
| Total |
225
|
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
|
#
|
PC Sub | Program Competencies/Outcomes |
* Contribution Level
|
||||
|
1
|
2
|
3
|
4
|
5
|
|||
| 1 |
To have an appropriate knowledge of methodological and practical elements of the basic sciences and to be able to apply this knowledge in order to describe engineering-related problems in the context of industrial systems. |
-
|
-
|
-
|
-
|
X
|
|
| 2 |
To be able to identify, formulate and solve Industrial Engineering-related problems by using state-of-the-art methods, techniques and equipment. |
-
|
-
|
X
|
-
|
-
|
|
| 3 |
To be able to use techniques and tools for analyzing and designing industrial systems with a commitment to quality. |
-
|
-
|
X
|
-
|
-
|
|
| 4 |
To be able to conduct basic research and write and publish articles in related conferences and journals. |
-
|
-
|
X
|
-
|
-
|
|
| 5 |
To be able to carry out tests to measure the performance of industrial systems, analyze and interpret the subsequent results. |
-
|
-
|
X
|
-
|
-
|
|
| 6 |
To be able to manage decision-making processes in industrial systems. |
-
|
X
|
-
|
-
|
-
|
|
| 7 |
To have an aptitude for life-long learning; to be aware of new and upcoming applications in the field and to be able to learn them whenever necessary. |
-
|
-
|
-
|
X
|
-
|
|
| 8 |
To have the scientific and ethical values within the society in the collection, interpretation, dissemination, containment and use of the necessary technologies related to Industrial Engineering. |
-
|
-
|
-
|
X
|
-
|
|
| 9 |
To be able to design and implement studies based on theory, experiments and modeling; to be able to analyze and resolve the complex problems that arise in this process; to be able to prepare an original thesis that comply with Industrial Engineering criteria. |
-
|
-
|
-
|
X
|
-
|
|
| 10 |
To be able to follow information about Industrial Engineering in a foreign language; to be able to present the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form. |
-
|
-
|
-
|
X
|
-
|
|
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
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