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•           Information on Degree Programmes

COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Optimization * ECMS   305 5 3 3 5

 Prerequisites and co-requisites Recommended Optional Programme Components None

Language of Instruction English
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Prof. Dr. Süleyman Bilgin KILIÇ
Instructors
 Dr. Öğr. Üyesi SEMİN PAKSOY 1. Öğretim Grup:A

Assistants
Goals
To give analytical thinking and problem-solving skills to the students by means of learning and application of the optimization methods
Content
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

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Explains Econometric concepts
X
2
Acquires basic Mathematics, Statistics and Operation Research concepts
X
3
Equipped with the foundations of Economics, and develops Economic models
X
4
Describes the necessary concepts of Business
X
5
Models problems with Mathematics, Statistics, and Econometrics
X
6
Estimates the model consistently and analyzes & interprets its results
X
7
Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems
X
8
Collects, edits, and analyzes data
X
9
Uses a package program of Econometrics, Statistics, and Operation Research
10
Effectively works, take responsibility, and the leadership individually or as a member of a team
X
11
Awareness towards life-long learning and follow-up of the new information and knowledge in the field of study
X
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
13
Uses Turkish and at least one other foreign language, academically and in the business context
14
Good understanding, interpretation, efficient written and oral expression of the people involved
X
15
Improves his/herself constantly by defining educational requirements considering interests and talents in scientific, cultural, art and social fields besides career development
16
Questions traditional approaches and their implementation while developing alternative study programs when required
17
Recognizes and implements social, scientific, and professional ethic values
X
18
Follows actuality, and interprets the data about economic and social events
X

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Introduction to the theory of optimization Students will be prepared by studying relevant subjects from the weekly program
2 Necessary and sufficient conditions for the global maximum or minimum of unrestricted functions Students will be prepared by studying relevant subjects from the weekly program
3 Newton-Raphson method Students will be prepared by studying relevant subjects from the weekly program
4 Constrained optimization of continuous functions Students will be prepared by studying relevant subjects from the weekly program
5 Lagrangian method in the form of equality constraints Students will be prepared by studying relevant subjects from the weekly program
6 Linear programming and the simplex method Students will be prepared by studying relevant subjects from the weekly program
7 The sensitivity analysis Students will be prepared by studying relevant subjects from the weekly program
8 Mid-term exam
9 Expansion of the Lagrangian method in the form inequality constraints Students will be prepared by studying relevant subjects from the weekly program
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 the weekly program
11 Non-linear programming algorithms Students will be prepared by studying relevant subjects from the weekly program
12 Gradient descent method Students will be prepared by studying relevant subjects from the weekly program
13 Quadratic programming Students will be prepared by studying relevant subjects from the weekly program
14 Geometric programming Students will be prepared by studying relevant subjects from the weekly program
15 Stochastic programming Students will be prepared by studying relevant subjects from the weekly program
16-17 Final examination