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•           Information on Degree Programmes

COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Introduction to Modeling and Optimization ENM   212 4 3 3 5

 Prerequisites and co-requisites Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Prof. Dr. Ali KOKANGÜL
Instructors
 Dr. Öğr. Üyesi YUSUF KUVVETLİ 1. Öğretim Grup:A

Assistants
Goals
To Define industrial problems and optimize them by using mathematical modelling techniques
Content
Identification of industrial problems, establishment of metamatic models, optimum solution derivation and sensitivity analysis by existing computer package programs to established models.

Learning Outcomes
1) What is optimization
2) Identification of optimization problems
3) Verbal description of the problem
4) Construct the mathematical model
5) Graphical solution of mathematical models
6) Linear programming
7) Midtermexam
8) Graphical solution method to nonlinearl programming models
9) Simplex method
10) Dual simplex method
11) Big-M method
12) Sensitivity analysis
13) Model building and solution derivation in LINGO package program
14) Sensitivity analysis in LINGO program
15) Sample optimization applications

Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Has sufficient background on topics related to mathematics, physical sciences and industrial engineering.
X
2
Gains ability to use the acquired theoretical knowledge on basic sciences and industrial engineering for describing, formulating and solving an industrial engineering problem, and to choose appropriate analytical and modeling methods.
X
3
Gains ability to analyze a service and/or manufacturing system or a process and describes, formulates and solves its problems .
X
4
Gains ability to choose and apply methods and tools for industrial engineering applications.
X
5
Can collect and analyze data required for industrial engineering problems ,develops and evaluates alternative solutions.
X
6
Works efficiently and takes responsibility both individually and as a member of a multi-disciplinary team.
X
7
Can access information and to search/use databases and other sources for information gathering.
X
8
Appreciates life time learning; follows scientific and technological developments and renews himself/herself continuously.
X
9
Can use computer software in industrial engineering along with information and communication technologies.
X
10
Can use oral and written communication efficiently.
X
11
Uses English skills to follow developments in industrial engineering and to communicate with people in his/her profession.
X
12
Has a conscious understanding of professional and ethical responsibilities.
X
13
Has a necessary consciousness on issues related to job safety and health, legal aspects of environment and engineering practice.
X
14
Becomes competent on matters related to project management, entrepreneurship, innovation and has knowledge about current matters in industrial engineering.
X

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 What is optimization Investigation of industrial problems Lecture
Discussion
Brain Storming
Case Study
Testing
Homework
Project / Design
2 Identification of optimization problems
3 Verbal description of the problem
4 Construct the mathematical model
5 Graphical solution of mathematical models
6 Linear programming
7 Midtermexam
8 Graphical solution method to nonlinearl programming models
9 Simplex method
10 Dual simplex method
11 Big-M yöntemi
12 Sensitivity analysis
13 Model building and solution derivation in LINGO package program
14 Sensitivity analysis in LINGO program
15 Sample optimization applications To find optimum solutions for industrial application problems
16-17 Final exam