Iğdır University Lifelong Learning Programme

Description of Individual Course Units

Course Unit Code	Course Unit Title	Type of Course Unit	Year of Study	Semester	Number of ECTS Credits
200401307001	DECISION MAKING METHODS	Elective	4	7	0

Level of Course Unit

First Cycle

Objectives of the Course

It is aimed to acquire effective decision-making knowledge and skills, and to gain competence and equipment for the acquisition and application of numerical methods used in managerial decision making.

Name of Lecturer(s)

Learning Outcomes

1	Gains the ability to make managerial decisions
2	Uses quantitative methods effective in making managerial decisions.
3	Defines the concept of cost and profit optimization.
4	Explain numerical methods with administrative methods.

Mode of Delivery

Daytime Class

Prerequisites and co-requisities

Non

Recommended Optional Programme Components

Course Contents

The concept of decision, factors affecting and limiting decision making, quantitative methods used in making decisions in businesses, decision problems, decision making models, decision making, numerical decision making methods are the content of the course.

Weekly Detailed Course Contents

Week	Theoretical	Practice	Laboratory
1	Decisions and models; structure of decision problems, purpose of decision, decision activities, uncontrollable activities
2	Uncertainty, uncertainty and risk, constraints, decision process
3	Model building and linear programming; Assumptions and definitions related to linear programming, properties of linear programming problem
4	Examples of the establishment of the linear programming model, the graphical solution technique of the linear programming model
5	Linear programming simplex method; standard and canonical forms, simplex method, types of simplex method applications; disruption unlimited solutions, optimal solution with options, no suitable solution found
6	Linear programming duality and sensitivity analysis; Definition of dual problem, propositions about primal and dual problems, dual simplex method, economic explanation of dual problem and shadow prices
7	Sensitivity analysis; change in cost row vector, change in column vector to the right of the constraining equation
8	Changing the constraint equation matrix, adding an activity, adding a new constraint. Mathematical model of the transportation problem, balanced and unbalanced transportation problems
9	Midterm
10	Transportation algorithm (solution technique); northwest corner method, least cost-to-eye method Vogel approach
11	Finding the most suitable solution; stepping stone method, reproducing method, deterioration situation and solution, optimal solutions with options
12	Maximization type transportation problems, sensitivity analysis in transportation models, sensitivity in costs
13	Maximum Flow Problems
14	Supply sensitivity, demand sensitivity, assignment model and the closest approximation method for the traveling salesman problem.

Recommended or Required Reading

Karar Verme Yöntemleri-Kaan Yaralıoğlu-Detay Yayıncılık Çok Kriterli Karar Verme Yöntemleri-Bahadır Fatih Yıldırım, Emrah Önder-Dora Yayıncılık

Planned Learning Activities and Teaching Methods

Assessment Methods and Criteria

Term (or Year) Learning Activities	Quantity	Weight
Midterm Examination	1	70
Individual Study for Mid term Examination	1	30
SUM		100
End Of Term (or Year) Learning Activities	Quantity	Weight
Final Examination	1	70
Individual Study for Final Examination	1	30
SUM		100
Term (or Year) Learning Activities		40
End Of Term (or Year) Learning Activities		60
SUM		100

Language of Instruction

Work Placement(s)

Workload Calculation

Activities	Number	Time (hours)	Total Work Load (hours)
Midterm Examination	1	1	1
Final Examination	1	1	1
Individual Study for Mid term Examination	1	1	1
Individual Study for Final Examination	1	1	1
TOTAL WORKLOAD (hours)			4

Contribution of Learning Outcomes to Programme Outcomes

	PO 1	PO 2	PO 3	PO 4	PO 5	PO 6
LO1	4	4	4	4	3	4
LO2	3	4	4	3	4	3
LO3	4	4	3	3	4	3
LO4	4	3	3	4	4	4

* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High