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IE 513 | Course Introduction and Application Information
| Course Name |
Mathematical Programming and Applications
|
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
|
IE 513
|
Fall
|
3
|
0
|
3
|
7.5
|
| Prerequisites |
None
|
|||||
| Course Language |
English
|
|||||
| Course Type |
Required
|
|||||
| 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 | Purpose of this course is to provide an overview of basic linear programming and discuss advanced modeling and solution techniques. |
| Learning Outcomes |
The students who succeeded in this course;
|
| Course Description | Topics of this course include theory, algorithms, and computational aspects of linear programming; formulation of problems as linear programs; duality and sensitivity analysis; primaldual simplex methods; the transportation, transshipment and assignment algorithms; extensions of linear programming; integer programming formulations and solution methods. |
|
|
Core Courses |
X
|
| Major Area Courses | ||
| 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 linear programming | Textbook Chapter 1 | |
| 2 | Geometric solution | Textbook Chapter 1 | |
| 3 | Linear algebra, convex analysis and polyhedral sets | Textbook Chapter 2 | |
| 4 | Simplex method | Textbook Chapter 3 | |
| 5 | Simplex method | Textbook Chapter 3 | |
| 6 | Simplex method | Textbook Chapter 3 | |
| 7 | Starting solution and convergence | Textbook Chapter 4 | |
| 8 | Special simplex implementations and optimality conditions | Textbook Chapter 5 | |
| 9 | Midterm exam | ||
| 10 | Duality | Textbook Chapter 6 | |
| 11 | Duality | Textbook Chapter 6 | |
| 12 | Sensitivitiy analysis | Textbook Chapter 6 | |
| 13 | Decomposition algorithms | Textbook Chapter 7 | |
| 14 | Integer Programming | ||
| 15 | New Year | ||
| 16 | Review of the Semester |
| Course Notes/Textbooks | Introduction to operations research. Hillier, F. S., & Lieberman, G. J., 10th edition, 2015, McGraw-Hill. |
| Suggested Readings/Materials | Linear programming and network flows. Bazaraa, M. S., Jarvis, J. J., & Sherali, H. D., 4th edition, 2011, John Wiley & Sons. |
EVALUATION SYSTEM
| Semester Activities | Number | Weigthing |
| Participation | ||
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques | ||
| Portfolio | ||
| Homework / Assignments |
20
|
|
| Presentation / Jury | ||
| Project |
1
|
15
|
| Seminar / Workshop | ||
| Oral Exams | ||
| Midterm |
1
|
25
|
| Final Exam |
1
|
40
|
| Total |
| Weighting of Semester Activities on the Final Grade |
3
|
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
|
6
|
84
|
| Field Work |
0
|
||
| Quizzes / Studio Critiques |
0
|
||
| Portfolio |
0
|
||
| Homework / Assignments |
0
|
||
| Presentation / Jury |
0
|
||
| Project |
1
|
33
|
33
|
| Seminar / Workshop |
0
|
||
| Oral Exam |
0
|
||
| Midterms |
1
|
25
|
25
|
| Final Exam |
1
|
35
|
35
|
| 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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