One of the most important responsibilities of managers in businesses is to make decisions. Today's competitive conditions require that optimal decisions be supported by numerical methods. The aim of this course is to gain the knowledge and skills to formulate a problem encountered in decision making, to establish the mathematical model, to obtain the solution from the model, to check and evaluate the model and its solution, to apply the obtained solution.
Prerequisite(s)
Course Code Course Name…
Corequisite(s)
Course Code Course Name…
Special Requisite(s)
The minimum qualifications that are expected from the students who want to attend the course.(Examples: Foreign language level, attendance, known theoretical pre-qualifications, etc.)
Instructor(s)
Assoc. Prof. Murat Taha Bilişik
Course Assistant(s)
Schedule
Monday, 16.00-18.00, CATS
Office Hour(s)
CATS CHAT ROOM
Teaching Methods and Techniques
-ppt, verbal lecturing, case studies
Principle Sources
-Taha , H.A. (Çeviri) Yöneylem Araştırması
Çağlar, Nazan,Yöneylem Araştırması, Türkmen kitabevi
Moore,J.H.(2001) Decision Modeling with Microsoft Excel
Other Sources
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Course Schedules
Week
Contents
Learning Methods
1. Week
Components of decision making, decision making without probabilities
Lecture, example using excel and class discussions
2. Week
Maximin,minimax, hurwicz criterion
Lecture, example using excel and class discussions
3. Week
Decision making with probabilities, expected value
Lecture, example using excel and class discussions
4. Week
Expected opportunity loss
Lecture, example using excel and class discussions
5. Week
Decision trees
Lecture, example using excel and class discussions
6. Week
Sequential decision tree analysis
Lecture, example using excel and class discussions
7. Week
Decision trees with posterior probabilities
Lecture, example using excel and class discussions
8. Week
Game theory
Lecture, example using excel and class discussions
9. Week
Markov analysis,states and state probabilities
Lecture, example using excel and class discussions
10. Week
Matrix of transition probabilities, predicting future market shares
Lecture, example using excel and class discussions
11. Week
Absorbing states and fundamental matrix: applications
Lecture, example using excel and class discussions
12. Week
Simulation, Monte Carlo process
Lecture, example using excel and class discussions
13. Week
Statistics analysis of simulation results
Lecture, example using excel and class discussions
Lecture, example using excel and class discussions)
16. Week
Final
Exam
17. Week
Final
Exam
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
40
Final Exam
1
60
Program Outcomes
PO-1
Comprehends both theoretical and applied subjects in international trade at the advanced level, and uses his/her knowledge when necessary.
PO-2
Analyses basic concepts and data related to International Trade and Economics by scientific methods, interprets those with analytically, and evaluates those with regard to economic issues.
PO-3
Express his/her thoughts, comments and evaluations related to International Trade discipline both in written and oral forms.
PO-4
Defines current problems, and proposes solutions which are supported by evidence and research based quantitative and qualitative data.
PO-5
Inspects how public and private sector enterprises engaged in trade activities operates in practice, and evaluates the continuities and the dynamism in these sectors.
PO-6
Defines and tracks local, regional (such as European Union or Middle East) and global issues from the point of political economics, and relates these issues to each other.
PO-7
Possesses sufficient knowledge in other disciplines related to International Trade (such as Economics, Finance, International Business and Law), and reports this information.
PO-8
Follows publications and research in International Trade, Globalisation and Financial Systems in the English language, and communicates with his/her colleagues internationally.
PO-9
Uses a second language (Russian, Chinese, etc.) at the intermediate level.
PO-10
Possesses ethical principles and scientific values in collection, interpretation and release of data.
Learning Outcomes
LO-1
To produce solutions to business problems using decision making techniques
LO-2
Will gain economic data evaluation structure with analytical thinking structure
LO-3
Will learn modeling and estimation by analyzing relations in economic data.
LO-4
To formulate a problem, to establish the mathematical model, to obtain the solution from the model, to check and evaluate the model and its solution, to gain the knowledge and ability to apply the obtained solution.
LO-5
Today's competitive conditions require that optimal decisions be supported by numerical methods.
