GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
OPTİMİZATİON TECHNİQUES/5341303
Course Title: OPTİMİZATİON TECHNİQUES
Credits 3 ECTS 7.5
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
learn basic optimization terms, modelling, concavity and convexity
constrained Geometric programming could be learned
Dynamic Programming could be learned
Inventory Problems could be solved
Linearization Techniques could be learned
Gives an ability to solve Searching Techniques (Povel, Hook Jeves and Advanced Gradiant Methods)
Stochastic Programming Techniques, Penalty Function Techniques and Nelder Mead Algoritm could be learned
Goal Programming could be learned
 -- MODE OF DELIVERY
  Face to Face education
 --WEEKLY SCHEDULE
1. Week  Basic optimization terms, modelling, concavity and convexity
2. Week  Classic Optimization
3. Week  Dynamic Programming
4. Week  Inventory Problems
5. Week  Linearization Techniques
6. Week  Povel Searching Technique
7. Week  Hook Jeves Searching Technique
8. Week  Advanced Gradiant Methods + Mid term exam
9. Week  Device Renovation
10. Week  Penalty Function Techniques
11. Week  Nelder Mead Algoritm
12. Week   Linear Goal Programming, Article presentation
13. Week   Study linear Programming in Data Envelopment Analysis, Article presentation
14. Week  Article presentation
15. Week  Final exam
16. Week  
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
25
 Assignment
5
25
 Application
5
25
 Projects
1
25
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
40
 Percentage of Final Exam to Total Score  
60
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
0
0
 Reading Tasks
10
3
30
 Searching in Internet and Library
10
3
30
 Material Design and Implementation
0
 Report Preparing
10
3
30
 Preparing a Presentation
5
3
15
 Presentation
5
3
15
 Midterm Exam and Preperation for Midterm Exam
3
3
9
 Final Exam and Preperation for Final Exam
4
4
16
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
187
 TOTAL WORKLOAD / 25: 
7.48
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
11. Based on the capabilities of undergraduate level, the students enrolled to the program can develop and deepen their knowledge and skill at the level of expertise on the same field of the undergradute study or a different field.X
22. The students use their theoretical and practical knowledge at the level of expertise in the area of statistics.X
33. The students should evaluate their acquired knowledge and skills in a critical perspective and the critical point of view guides their learning process.X
44. Theoretical and practical knowledge gained in graduate level in the field of Statistics should be applied and transfer to the current problems.X
55. By performing the process from the identification of the scientific research problem to reporting and the process should be transferred in oral, written and visual ways.X
66. The students should use computer software and information technologies on the level required by the field of Statistics.X
77. The students should have the ability to use Statistics in interdisciplinary studies.X
88. The students should have enough foreign language level to pursue statistical literature.X
99. At the required level of field of statistics, he/she should use statistical software and information technology efficiently in a such a way that helps solving problems in his/her research.X
1010. In the process of applying knowledge in a professional sense, social, scientific, and ethical values should be regarded.X
 -- NAME OF LECTURER(S)
   (Prof. Dr. Hasan BAL)
 -- WEB SITE(S) OF LECTURER(S)
   (http://websitem.gazi.edu.tr/site/hasanbal)
 -- EMAIL(S) OF LECTURER(S)
   (hasanbal@gazi.edu.tr)