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Information
| Unit | FACULTY OF SCIENCE AND LETTERS |
| STATISTICS PR. | |
| Code | ISB222 |
| Name | Optimization Techniques - II |
| Term | 2021-2022 Academic Year |
| Semester | 4. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 5 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Label | C Compulsory |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. NİMET ÖZBAY |
| Course Instructor |
Doç. Dr. NİMET ÖZBAY
(Bahar)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
to solve unconstrained and constrained optimization problems, to learn search methods
Course Content
Unrestricted problems, equality restricted optimization problems, inequality restricted optimization problems, nonlinear programming, single and multi variable unrestricted optimization methods, restricted optimization methods, geometric programming, target programming.
Course Precondition
Yok
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | understand unconstrained optimization the problems and solutions |
| LO02 | use unrestricted multivariate methods for the solution of optimization problems |
| LO03 | understand the multi-dimensional optimization problems with equality constraints |
| LO04 | apply Jacobian and the methods of Lagrange |
| LO05 | Understand inequality constrained optimization problems |
| LO06 | Write and solve the Kuhn-Tucker Conditions |
| LO07 | understand search methods, to distinguish the relationship between them |
| LO08 | apply search methods for solving optimization problems |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explain the essence fundamentals and concepts in the field of Statistics | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Emphasize the importance of Statistics in life | 3 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Define basic principles and concepts in the field of Law and Economics | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Produce numeric and statistical solutions in order to overcome the problems | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Use proper methods and techniques to gather and/or to arrange the data | 2 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Utilize computer programs and builds models, solves problems, does analyses and comments about problems concerning randomization | |
| PLO07 | Bilgi - Kuramsal, Olgusal | Apply the statistical analyze methods | 3 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Make statistical inference (estimation, hypothesis tests etc.) | |
| PLO09 | Bilgi - Kuramsal, Olgusal | Generate solutions for the problems in other disciplines by using statistical techniques and gain insight | |
| PLO10 | Bilgi - Kuramsal, Olgusal | Discover the visual, database and web programming techniques and posses the ability of writing programs | |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Distinguish the difference between the statistical methods | |
| PLO12 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Make oral and visual presentation for the results of statistical methods | 3 |
| PLO13 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Have capability on effective and productive work in a group and individually | 2 |
| PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs | 2 |
| PLO15 | Yetkinlikler - Öğrenme Yetkinliği | Develop scientific and ethical values in the fields of statistics-and scientific data collection |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Unconstrained Optimization | Source reading | |
| 2 | Unrestricted Multivariable Optimization | Source reading | |
| 3 | Unrestricted Multivariable Optimization | Source reading | |
| 4 | Multidimensional Equality Constrained Optimization Problems | Source reading | |
| 5 | Multidimensional Equality Constrained Optimization Problems | Source reading | |
| 6 | Inequality Constrained Optimization Problems | Source reading | |
| 7 | Kuhn-Tucker conditions | Source reading | |
| 8 | Mid-Term Exam | Review the topics discussed in the lecture notes and sources | |
| 9 | Univariate Search Techniques | Source reading | |
| 10 | Full Search, Search Two Points of Symmetric | Source reading | |
| 11 | Fibonacci Searchı | Source reading | |
| 12 | Search Two Points of Symmetric | Source reading | |
| 13 | Golden Ratio Search | Source reading | |
| 14 | Split into three Search | Source reading | |
| 15 | Problem Solving | Source reading | |
| 16 | Term Exams | Review the topics discussed in the lecture notes and sources | |
| 17 | Term Exams | Review the topics discussed in the lecture notes and sources |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 100 | 40 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 12 | 12 |
| Final Exam | 1 | 18 | 18 |
| Total Workload (Hour) | 114 | ||
| Total Workload / 25 (h) | 4,56 | ||
| ECTS | 5 ECTS | ||