| Teaching Staff
|
Prof. Dr. Cenap ERDEMİR |
| Language of Instruction |
Türkçe (Turkish) |
| Type Of Course |
Compulsory |
| Prerequisites |
MAT 101
MAT 102 |
| Recommended Optional Programme Component |
|
| Course Objectives |
Introduction to mathematical programming and examples, construction of linear programming models, the geometrical interpretation of solutions to the linear programming problems and their algebraic groundwork, the simplex method, the use of artificial variables. duality theory, dual simplex method, the transportation problem, the relationship between game theory and linear programming. |
| Course Content |
1. Management sciense and modelling, decision making process, introduction to linear programming.
2. Formulation of linear programming models, Solutions by graphical methods
3. Formulation of linear programming models on Excel and solving the models by SOLVER .
4. Some linear programming models for marketing and finances.
5. Üretim/satın alma ve üretim/karışım uygulamaları Production, purchasing and
6. Dynamic or time dependent problems: Cash flow problem and other applications.
7. Genel doğrusal programlama model uygulamaları Genaral linear programming models
8. Ara sınav
9. Sensitivity analysis
10. Network models : Description, tools and terminology. Transportation models.
11. Assigment problems.
12. Multi-period production planning models.
13. Shortest path models.
14. Maximal flow and minimum spanning tree models
|
| Learning Outcomes (LO) |
The students who attended the course and were successful at the end of semester will acquire the followings; 1- will be able to construct mathematical model of the problem, 2- will be able to find an optimal using by softwares, 3- will be able to perform a sensitivity analysis, 4- will be able to apply linear programming methods to each areas of managemet science.
|
| Mode of Delivery |
Face to face |
| Course Outline |
| Week |
Topics |
| 1. Week |
1. Management sciense and modelling, decision making process, introduction to linear programming.
|
| 2. Week |
2. Formulation of linear programming models, Solutions by graphical methods
|
| 3. Week |
3. Formulation of linear programming models on Excel and solving the models by SOLVER .
|
| 4. Week |
4. Some linear programming models for marketing and finance areas.
|
| 5. Week |
5. Üretim/satın alma ve üretim/karışım uygulamaları Production, purchasing and
|
| 6. Week |
6. Dynamic or time dependent problems: Cash flow problem and other applications.
|
| 7. Week |
7. Genel doğrusal programlama model uygulamaları Genaral linear programming models
|
| 8. Week |
Midterm exam |
| 9. Week |
9. Sensitivity analysis
|
| 10. Week |
10. Network models : Description, tools and terminology. Transportation models.
|
| 11. Week |
11. Assigment problems.
|
| 12. Week |
12. Multi-period production planning models.
|
| 13. Week |
13. Shortest path models.
|
| 14. Week |
14. Maximal flow and minimum spanning tree models
|
|
| Assessment |
| |
Percentage(%) |
| Mid-term (%) |
40 |
| Quizes (%) |
|
| Homeworks/Term papers (%) |
|
| Practice (%) |
|
| Labs (%) |
|
| Projects/Field Work (%) |
|
| Seminars/Workshops (%) |
|
| Final (%) |
60 |
| Other (%) |
|
| Total(%) |
100 |
|
| Course Book (s) and/or References |
1. Ulucan, Aydın, 2007, Yöneylem Araştırması, İşletmecilik Uygulamalı Bilgisayar Destekli Modelleme, Siyasal Kitapevi Ankara.
2.. Taha, H., 2010, Yöneylem Araştırması; 6. Basımdan Çeviri , Literatür Yayıncılık, İstanbul.
3. Winston, W. L., 2003, Operational Research Applications and Algorithms.
4. Hillier, F.S., Lieberman G.J., 2004, Introduction to Operational Research, McGraw-Hill.
|
| Work Placement(s) |
|
| The Relationship between Program Qualifications (PQ) and Course Learning Outcomes (LO) |
| PQ1 | PQ2 | PQ3 | PQ4 | PQ5 | PQ6 | PQ7 | PQ8 | PQ9 | PQ10 | PQ11 | PQ12 | PQ13 | PQ14 | LO1 | 2 | 5 | | | | | 2 | | | | | | | | LO2 | | 5 | | | | | 2 | | | | | | | | LO3 | | 5 | | | | | | | | | | | | | LO4 | | 5 | | | | | | | | | | | | |
* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High |