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Information
| Unit | FACULTY OF SCIENCE AND LETTERS |
| STATISTICS PR. | |
| Code | ISB221 |
| Name | Optimization Techniques - I |
| Term | 2016-2017 Academic Year |
| Semester | 3. 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 |
Prof. Dr. SELAHATTİN KAÇIRANLAR
(Güz)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
To establish a model for Linear Programming Problems and established methods to solve a variety of models, to solve Dual model , to learn Transportation models
Course Content
Hyperplanes, convex sets, introduction to Linear Programming Problem (LPP), geometric solutions, the simplex method, duality, relations between the primal and dual problems, the dual simplex method, sensitivity analysis, transportation problem, assignment problem.
Course Precondition
Yok
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Describes the properties of the linear programming problem |
| LO02 | Builds the linear programming model, solves this problem by graphical and analytical methods |
| LO03 | Uses the simplex solution method |
| LO04 | Distinguish the difference between the simplex and two phase methods |
| LO05 | Uses the two phase method |
| LO06 | Uses the Big M method |
| LO07 | Write dual of the linear programming model |
| LO08 | Solves balanced and unbalanced transportation models |
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 | 4 |
| 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 | 4 |
| 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 | 4 |
| 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 | Definitions with DP , Examples, and Model Building on DP | Source reading | |
| 2 | Hyper Planes, Convex Sets, Convex Linear Functions on Sets | Source reading | |
| 3 | Graphical Solution Methods | Source reading | |
| 4 | Gauss Jordan Reduction, the canonical form for DPP | Source reading | |
| 5 | Analytical Solution | Source reading | |
| 6 | Simplex Solution Method | Source reading | |
| 7 | Two-Phase Method (First phase) | Source reading | |
| 8 | Midterm exam | Review the topics discussed in the lecture notes and sources | |
| 9 | Two-Phase Method (Two phase) | Source reading | |
| 10 | Big M method | Source reading | |
| 11 | The dual of the linear model, Relationships the original models and Dual Between Solutions | Source reading | |
| 12 | Dual Simplex Method | Source reading | |
| 13 | Transportation Model, Solution Methods | Source reading | |
| 14 | to take advantage of the package programs that the solution of Models | Source reading | |
| 15 | Problem solving | Source reading | |
| 16 | Final exam | Review the topics discussed in the lecture notes and sources | |
| 17 | Final exam | 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 | 10 | 3 | 30 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 10 | 10 |
| Final Exam | 1 | 10 | 10 |
| Total Workload (Hour) | 134 | ||
| Total Workload / 25 (h) | 5,36 | ||
| ECTS | 5 ECTS | ||