FACULTY OF ENGINEERING

Department of Mechatronics Engineering

IE 357 | Course Introduction and Application Information

Course Name
Special Topics in Optimization
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
IE 357
Fall/Spring
3
0
3
6

Prerequisites
  IE 252 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Service Course
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course Lecture / Presentation
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives To teach students optimization methods and modelling techniques not taught in compulsory courses
Learning Outcomes The students who succeeded in this course;
  • Will be able to describe the limitations of classical optimization methods
  • Will be able to model production management and industrial systems engineering field problems using these methods
  • Will be able to model production management and industrial systems engineering field problems using dynamic programming
  • Will be able to model production management and industrial systems engineering field problems using hybrid optimization methods
  • Will be able to solve these production management and industrial systems engineering field problems models' using appropriate software
Course Description In this course, students will have the chance to learn certain optimization subjects, methods and models which are not covered in compulsory courses. At the end students will also have the chance to learn applications of these models and methods.

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Fundamentals of Optimization Review Lecture Notes
2 Large Scale Optimization Solution methods LP Relaxation Lecture Notes
3 Large Scale Optimization Solution methods LP Relaxation Lecture Notes
4 Large Scale Optimization Solution methods Dantzig Wolfe Lecture Notes
5 Large Scale Optimization Solution methods B&B Lecture Notes
6 Large Scale Optimization Solution methods B&B Lecture Notes
7 Large Scale Optimization Solution methods Lagrangian Relaxation Lecture Notes
8 Large Scale Optimization Solution methods Lagrangian Relaxation Lecture Notes
9 Midterm
10 Large Scale Optimization Solution methods Cutting Plane Lecture Notes
11 Large Scale Optimization Solution methods Bender Decomposition Lecture Notes
12 Dynamic Programming Lecture Notes
13 Dynamic Programming Lecture Notes
14 Dynamic Programming Lecture Notes
15 Review and Presentations Lecture Notes
16 Review of the Semester  

 

Course Notes/Textbooks
Suggested Readings/Materials

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exams
Midterm
2
60
Final Exam
1
40
Total

Weighting of Semester Activities on the Final Grade
60
Weighting of End-of-Semester Activities on the Final Grade
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
0
Study Hours Out of Class
14
4
56
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
0
Presentation / Jury
0
Project
0
Seminar / Workshop
0
Oral Exam
0
Midterms
2
22
44
Final Exam
1
32
32
    Total
180

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have knowledge in Mathematics, science, physics knowledge based on mathematics; mathematics with multiple variables, differential equations, statistics, optimization and linear algebra; to be able to use theoretical and applied knowledge in complex engineering problems

2

To be able to identify, define, formulate, and solve complex mechatronics engineering problems; to be able to select and apply appropriate analysis and modeling methods for this purpose.

3

To be able to design a complex electromechanical system, process, device or product with sensor, actuator, control, hardware, and software to meet specific requirements under realistic constraints and conditions; to be able to apply modern design methods for this purpose.

4

To be able to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in Mechatronics Engineering applications; to be able to use information technologies effectively.

5

To be able to design, conduct experiments, collect data, analyze and interpret results for investigating Mechatronics Engineering problems.

6

To be able to work effectively in Mechatronics Engineering disciplinary and multidisciplinary teams; to be able to work individually.

7

To be able to communicate effectively in Turkish, both in oral and written forms; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions.

8

To have knowledge about global and social impact of engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of engineering solutions.

9

To be aware of ethical behavior, professional and ethical responsibility; information on standards used in engineering applications.

10

To have knowledge about industrial practices such as project management, risk management and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

11

Using a foreign language, he collects information about Mechatronics Engineering and communicates with his colleagues. ("European Language Portfolio Global Scale", Level B1)

12

To be able to use the second foreign language at intermediate level.

13

To recognize the need for lifelong learning; to be able to access information; to be able to follow developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Mechatronics Engineering.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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