Undergraduate
Faculty of Science and Letters
Mathematics And Computer Science
Anlık RSS Bilgilendirmesi İçin Tıklayınız.Düzenli bilgilendirme E-Postaları almak için listemize kaydolabilirsiniz.


Operations Research

Course CodeSemester Course Name LE/RC/LA Course Type Language of Instruction ECTS
MB0042 Operations Research 2/2/0 DE Turkish 5
Course Goals
To model of the problem that we encounter in our environment, to find the solution of the model, to check the model and the solution and analyze them. To teach how to use the sources in effective way.
 
Prerequisite(s) None
Corequisite(s) None
Special Requisite(s) -
Instructor(s) Assoc. Prof. Ozan KOCADAĞLI
Course Assistant(s) -
Schedule Wednesday, 17:00 - 18:50, CATsV3.0 Meetings Friday, 11:00 - 12:50, CATsV3.0 Meetings
Office Hour(s) Friday, 10:00-11:00, CATsV3.0 Chatroom
Teaching Methods and Techniques -Resitation and Oral Presantation
Principle Sources --Yöneylem Araştırması, Nalan Cinemre
-Doğrusal Programlama, Nalan Cinemre
Other Sources - Yöneylem Araştırması (Hamdy A. Taha) Çeviren: Ş. Alp Baray- Şakir Esnaf

-Operations Research: Applications and Algorithms, Wayne L. Winston, 4th edition, Thomson Brook/Cole, 2004.
Course Schedules
Week Contents Learning Methods
1. Week Introduction to linear programming Resitation and Oral Presentation
2. Week Establishing the linear programming model Resitation and Oral Presentation
3. Week Solution of graphs Resitation and Oral Presentation
4. Week Sensitivity Analysis on graph solution Resitation and Oral Presentation
5. Week Simplex method Resitation and Oral Presentation
6. Week M method Resitation and Oral Presentation
7. Week Two Step Method Resitation and Oral Presentation
8. Week Midterm Midterm
9. Week Special cases on simplex methods Resitation and Oral Presentation
10. Week Duality and economic comment Resitation and Oral Presentation
11. Week Primal Dual Calculations-Sensitivity Analysis Resitation and Oral Presentation
12. Week Definition of Transport Model Resitation and Oral Presentation
13. Week Various Transportation Models Resitation and Oral Presentation
14. Week Game Theory/Desicion Theory Resitation and Oral Presentation
15. Week
16. Week
17. Week
Assessments
Evaluation tools Quantity Weight(%)
Midterm(s) 1 40
Final Exam 1 60


Program Outcomes
PO-1Interpreting advanced theoretical and applied knowledge in Mathematics and Computer Science.
PO-2Critiquing and evaluating data by implementing the acquired knowledge and skills in Mathematics and Computer Science.
PO-3Recognizing, describing, and analyzing problems in Mathematics and Computer Science; producing solution proposals based on research and evidence.
PO-4Understanding the operating logic of computer and recognizing computational-based thinking using mathematics as a discipline.
PO-5Collaborating as a team-member, as well as individually, to produce solutions to problems in Mathematics and Computer Science.
PO-6Communicating in a foreign language, and interpreting oral and written communicational abilities in Turkish.
PO-7Using time effectively in inventing solutions by implementing analytical thinking.
PO-8Understanding professional ethics and responsibilities.
PO-9Having the ability to behave independently, to take initiative, and to be creative.
PO-10Understanding the importance of lifelong learning and developing professional skills continuously.
PO-11Using professional knowledge for the benefit of the society.
Learning Outcomes
LO-1Establishes linear programming model and makes sensitivity analysis.
LO-2Understands special cases of simplex method., M method and the two-step method and will be able to apply them.
LO-3Understands game theory/decision theory.
LO-4Understands duality and sensitivity analysis.
LO-5Understands transportation modes and types.
Course Assessment Matrix:
Program Outcomes - Learning Outcomes Matrix
 PO 1PO 2PO 3PO 4PO 5PO 6PO 7PO 8PO 9PO 10PO 11
LO 1
LO 2
LO 3
LO 4
LO 5