GRADUATE SCHOOL
M.SC. In Industrial Engineering (With Thesis)
IE 535 | Course Introduction and Application Information
Course Name |
Advanced Network Optimization
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
IE 535
|
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 | - | |||||
Course Coordinator | - | |||||
Course Lecturer(s) | - | |||||
Assistant(s) | - |
Course Objectives | |
Learning Outcomes |
The students who succeeded in this course;
|
Course Description | Topics of this course include the shortest path problem, the maximum flow problem, the minimum cost flow problem, the minimum spanning tree problem and dynamic programming. |
|
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 | Notation and definitions. Paths, trees and cycles | Textbook Chapter 2 |
2 | Shortest paths | Textbook Chapter 4 |
3 | Shortest paths | Textbook Chapter 5 |
4 | Maximum flows | Textbook Chapter 6 |
5 | Maximum flows | Textbook Chapter 7 and 8 |
6 | Minimum spanning trees | Textbook Chapter 13 |
7 | Minimum cost flows | Textbook Chapter 9 and 10 |
8 | Minimum cost flows | Textbook Chapter 11 |
9 | Multi-commodity flow problem | Textbook Chapter 17 |
10 | Midterm | |
11 | Introduction to Dynamic Programming | Denardo |
12 | Deterministic Dynamic programming | Denardo |
13 | Deterministic Dynamic programming | Denardo |
14 | Stochastic Dynamic Programming | Denardo |
15 | Stochastic Dynamic Programming | Denardo |
16 | Stochastic Dynamic Programming | Denardo |
Course Notes/Textbooks | Ravindra K. Ahuja, Thomas L. Magnanti, James B. Orlin, Network Flows: Theory, Algorithms, and Applications, Prentice Hall Instructor notes and lecture slides. |
Suggested Readings/Materials | Eric V. Denardo, Dynamic Programming Models and Applications, Prentice Hall |
EVALUATION SYSTEM
Semester Activities | Number | Weigthing |
Participation | ||
Laboratory / Application | ||
Field Work | ||
Quizzes / Studio Critiques | ||
Portfolio | ||
Homework / Assignments |
4
|
40
|
Presentation / Jury | ||
Project | ||
Seminar / Workshop | ||
Oral Exams | ||
Midterm |
1
|
30
|
Final Exam |
1
|
30
|
Total |
Weighting of Semester Activities on the Final Grade |
60
|
|
Weighting of End-of-Semester Activities on the Final Grade |
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 |
15
|
6
|
90
|
Field Work |
0
|
||
Quizzes / Studio Critiques |
0
|
||
Portfolio |
0
|
||
Homework / Assignments |
4
|
10
|
40
|
Presentation / Jury |
0
|
||
Project |
0
|
||
Seminar / Workshop |
0
|
||
Oral Exam |
0
|
||
Midterms |
1
|
20
|
20
|
Final Exam |
1
|
27
|
27
|
Total |
225
|
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
#
|
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