GRADUATE SCHOOL

M.SC. in Computer Engineering (With Thesis)

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/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 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;
  • Be able to formulate engineering problems as mathematical programs
  • Be able to solve mathematical problems using appropriate methods
  • Be able to apply mathematical programming and solution methods to real life problems like network flow
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.

 



Course Category

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 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 Bazaraa M.S., Jarvis J.J., Sherali H.D., Linear Programming and Network Flows, Wiley. Bertsimas, D. and Tsitsiklis, J. N., Introduction to Linear Optimization, Athena Scientific, 1997, Instructor notes and lecture slides.
Suggested Readings/Materials Related Research Papers

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
20
Presentation / Jury
Project
1
25
Seminar / Workshop
Oral Exams
Midterm
1
25
Final Exam
1
30
Total

Weighting of Semester Activities on the Final Grade
3
70
Weighting of End-of-Semester Activities on the Final Grade
1
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
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

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1 Accesses information in breadth and depth by conducting scientific research in Computer Engineering; evaluates, interprets and applies information.
2 Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.
3 Uses scientific methods to complete and apply information from uncertain, limited or incomplete data; can combine and use information from different disciplines.
4 Is informed about new and upcoming applications in the field and learns them whenever necessary.
5 Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.
6 Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs
7 Designs and implements studies based on theory, experiments and modelling; analyses and resolves the complex problems that arise in this process.
8 Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations; can work independently and takes responsibility.
9 Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.
10 Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.
11 Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications.
12 Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.

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

 


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