| Course Description |
|
| Course Name |
: |
Optimization Methods |
|
| Course Code |
: |
EM 206 |
|
| Course Type |
: |
Optional |
|
| Level of Course |
: |
First Cycle |
|
| Year of Study |
: |
2 |
|
| Course Semester |
: |
Spring (16 Weeks) |
|
| ECTS |
: |
4 |
|
| Name of Lecturer(s) |
: |
Assoc.Prof.Dr. S.BİLGİN KILIÇ
Asst.Prof.Dr. SEMİN PAKSOY
|
|
| Learning Outcomes of the Course |
: |
Gives students the analytical thinking and problem solving skills
Provides insights to the importance of the optimum solution in economic problems
Provides the learning of methods for the solution of unconstrained and constrained optimization problems
Develops the ability to apply different optimization algorithms to relevant problems
|
|
| Mode of Delivery |
: |
Face-to-Face |
|
| Prerequisites and Co-Prerequisites |
: |
None |
|
| Recommended Optional Programme Components |
: |
None |
|
| Aim(s) of Course |
: |
To give analytical thinking and problem-solving skills to the students by means of learning and application of the optimization methods |
|
| Course Contents |
: |
Introduction to the theory of optimization, necessary and sufficient conditions for the global maximum or minimum of unrestricted functions, Newton-Raphson method, constrained optimization of continuous functions, lagrangian method in the form of equality constraints, linear programming and the simplex method, sensitivity analysis, expansion of the Lagrangian method in the form inequality constraints, determination of the Kuhn-Tucker necessary and sufficient conditions for the non-linear constrained problems, non-linear programming algorithms; gradient descent method, quadratic programming, geometric programming and stochastic programming |
|
| Language of Instruction |
: |
Turkish |
|
| Work Place |
: |
Classroom |
|
|
Course Outline /Schedule (Weekly) Planned Learning Activities |
| Week | Subject | Student's Preliminary Work | Learning Activities and Teaching Methods |
|
1 |
Introduction to the theory of optimization
|
Students will be prepared by studying relevant subjects from source books according to the weekly program |
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab |
|
2 |
Necessary and sufficient conditions for the global maximum or minimum of unrestricted functions |
Students will be prepared by studying relevant subjects from source books according to the weekly program |
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab |
|
3 |
Newton-Raphson method |
Students will be prepared by studying relevant subjects from source books according to the weekly program |
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab |
|
4 |
Constrained optimization of continuous functions |
Students will be prepared by studying relevant subjects from source books according to the weekly program
|
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab |
|
5 |
Lagrangian method in the form of equality constraints |
Students will be prepared by studying relevant subjects from source books according to the weekly program
|
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab |
|
6 |
Linear programming and the simplex method |
Students will be prepared by studying relevant subjects from source books according to the weekly program
|
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab |
|
7 |
The sensitivity analysis |
Students will be prepared by studying relevant subjects from source books according to the weekly program
|
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab |
|
8 |
Mid-term exam |
- |
- |
|
9 |
Expansion of the Lagrangian method in the form inequality constraints |
Students will be prepared by studying relevant subjects from source books according to the weekly program
|
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab
|
|
10 |
Determination of the Kuhn-Tucker necessary and sufficient conditions for the non-linear constrained problems
|
Students will be prepared by studying relevant subjects from source books according to the weekly program
|
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab
|
|
11 |
Non-linear programming algorithms
|
Students will be prepared by studying relevant subjects from source books according to the weekly program
|
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab |
|
12 |
Gradient descent method
|
Students will be prepared by studying relevant subjects from source books according to the weekly program
|
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab |
|
13 |
Quadratic programming
|
Students will be prepared by studying relevant subjects from source books according to the weekly program
|
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab |
|
14 |
Geometric programming |
Students will be prepared by studying relevant subjects from source books according to the weekly program
|
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab |
|
15 |
Stochastic programming |
Students will be prepared by studying relevant subjects from source books according to the weekly program
|
The theoretical issues discussed in classrooms and the application of problem solving will be made in the computer lab |
|
16/17 |
Final examination |
- |
- |
|
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| Contribution of the Course to Key Learning Outcomes |
| # | Key Learning Outcome | Contribution* |
|
1 |
Models problems with Mathematics, Statistics, and Econometrics |
5 |
|
2 |
Explains Econometric concepts |
4 |
|
3 |
Estimates the model consistently and analyzes & interprets its results |
5 |
|
4 |
Acquires basic Mathematics, Statistics and Operation Research concepts |
5 |
|
5 |
Equipped with the foundations of Economics, and develops Economic models |
4 |
|
6 |
Describes the necessary concepts of Business |
3 |
|
7 |
Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems |
5 |
|
8 |
Collects, edits, and analyzes data |
3 |
|
9 |
Uses a package program of Econometrics, Statistics, and Operation Research |
4 |
|
10 |
Effectively works, take responsibility, and the leadership individually or as a member of a team |
2 |
|
11 |
Awareness towards life-long learning and follow-up of the new information and knowledge in the field of study |
2 |
|
12 |
Develops the ability of using different resources in the form of academic rules, synthesis the information gathered, and effective presentation in an area which has not been studied |
3 |
|
13 |
Uses Turkish and at least one other foreign language, academically and in the business context |
2 |
|
14 |
Good understanding, interpretation, efficient written and oral expression of the people involved |
4 |
|
15 |
Questions traditional approaches and their implementation while developing alternative study programs when required |
4 |
|
16 |
Recognizes and implements social, scientific, and professional ethic values |
3 |
|
17 |
Follows actuality, and interprets the data about economic and social events |
3 |
|
18 |
Improves himself/herself constantly by defining educational requirements considering interests and talents in scientific, cultural, art and social fields besides career development |
3 |
| * Contribution levels are between 0 (not) and 5 (maximum). |
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