COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Optimization Techniques - I * ISB   221 3 3 3 5

Prerequisites and co-requisites Yok
Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Prof.Dr. Selahattin KAÇIRANLAR
Instructors
Prof.Dr.SELAHATTİN KAÇIRANLAR1. Öğretim Grup:A
Prof.Dr.SELAHATTİN KAÇIRANLAR2. Öğretim Grup:A
 
Assistants
Goals
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
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.

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics
2
Emphasize the importance of Statistics in life
3
Define basic principles and concepts in the field of Law and Economics
4
Produce numeric and statistical solutions in order to overcome the problems
5
Use proper methods and techniques to gather and/or to arrange the data
6
Utilize computer systems and softwares
7
Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events
8
Apply the statistical analyze methods
9
Make statistical inference(estimation, hypothesis tests etc.)
10
Generate solutions for the problems in other disciplines by using statistical techniques
11
Discover the visual, database and web programming techniques and posses the ability of writing programme
12
Construct a model and analyze it by using statistical packages
13
Distinguish the difference between the statistical methods
14
Be aware of the interaction between the disciplines related to statistics
15
Make oral and visual presentation for the results of statistical methods
16
Have capability on effective and productive work in a group and individually
17
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
18
Develop scientific and ethical values in the fields of statistics-and scientific data collection

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
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
16-17 Final exam Review the topics discussed in the lecture notes and sources

Recommended or Required Reading
Textbook
Additional Resources