ISB221 Optimization Techniques - I

5 ECTS - 3-0 Duration (T+A)- 3. Semester- 3 National Credit

Information

Unit FACULTY OF SCIENCE AND LETTERS
STATISTICS PR.
Code ISB221
Name Optimization Techniques - I
Term 2018-2019 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 DP problem
LO02 Builds model, uses a graphical and analytical methods of solution
LO03 Use the Simplex Solution Method
LO04 Distinguish the difference Simplex method between the two-phase method
LO05 Uses the Two-Phase Method
LO06 Uses Big M Method
LO07 Write Dual of the linear model , distinguishes the relationship between the original and the Dual models Solutions
LO08 Apply Dual Simplex Method
LO09 Write Balanced and unbalanced transportation model, apply the methods of solution
LO10 Use Package in solving models


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 - Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics 3
PLO02 - Emphasize the importance of Statistics in life 4
PLO03 - Define basic principles and concepts in the field of Law and Economics 0
PLO04 - Produce numeric and statistical solutions in order to overcome the problems 3
PLO05 - Use proper methods and techniques to gather and/or to arrange the data 2
PLO06 - Utilize computer systems and softwares 4
PLO07 - Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events 5
PLO08 - Apply the statistical analyze methods 3
PLO09 - Make statistical inference(estimation, hypothesis tests etc.) 2
PLO10 - Generate solutions for the problems in other disciplines by using statistical techniques 2
PLO11 - Discover the visual, database and web programming techniques and posses the ability of writing programme 0
PLO12 - Construct a model and analyze it by using statistical packages 4
PLO13 - Distinguish the difference between the statistical methods 3
PLO14 - Be aware of the interaction between the disciplines related to statistics 4
PLO15 - Make oral and visual presentation for the results of statistical methods 3
PLO16 - Have capability on effective and productive work in a group and individually 3
PLO17 - 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 1
PLO18 - Develop scientific and ethical values in the fields of statistics-and scientific data collection 1


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 Mid-Term 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 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

Update Time: 29.04.2025 02:17