COURSE INTRODUCTION AND APPLICATION INFORMATION


Course Name
Multi Objective Optimization
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
IE 515
Fall/Spring
3
0
3
7.5
Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
Second Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course
Course Coordinator
Course Lecturer(s) -
Assistant(s) -
Course Objectives The objective of this course is to present the idea of multiple objectives and techniques used and equip the student with the skills that will help them to make decisions where multiple conflicting criterias involved.
Learning Outcomes The students who succeeded in this course;
  • Learn the multi objective optimization methods
  • Identify the multi objective optimization method to pply a problem
  • Apply the multi objective decision making methods to real life problems
Course Description Topics include overview and definitions of Multiple Criteria Decision Making (MCDM) concept; decision space, objective space, convex sets, functions and test for convexity; formulation of the general multiple criteria programming, classification of multiple criteria programming methods, decision making with discrete and continuous alternatives; goal programming and algorithms for goal programming.
Related Sustainable Development Goals

 



Course Category

Core Courses
Major Area Courses
X
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Introduction, Definitions
2 Discrete Alternative Problem, Convex Dominated and Adjacent Efficient Solutions, Analytical Hierarchy Process
3 Discrete alternative problem, Presentation Related paper
4 Utility functions
5 Cones
6 Ranking, Classificaiton and Sorting, Presentation Related paper
7 Presentations Related papers
8 Midterm
9 Interactive methods, Data Envelopment Analysis
10 Presentations Related papers
11 Continuous solution space, Presentation Related paper
12 Continuous solution space
13 Continuous solution space
14 Review
15 -
16 -
Course Notes/Textbooks Course notes
Suggested Readings/Materials Related Research Papers

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
1
5
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
4
20
Presentation / Jury
1
20
Project
Seminar / Workshop
Oral Exam
Midterm
1
25
Final Exam
1
30
Total

Weighting of Semester Activities on the Final Grade
70
Weighting of End-of-Semester Activities on the Final Grade
30
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
Study Hours Out of Class
15
5
75
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
4
12
Presentation / Jury
1
10
Project
Seminar / Workshop
Oral Exam
Midterms
1
20
Final Exams
1
24
    Total
225

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

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

To have an appropriate knowledge of methodological and practical elements of the basic sciences and to be able to apply this knowledge in order to describe engineering-related problems in the context of industrial systems.

X
2

To be able to identify, formulate and solve Industrial Engineering-related problems by using state-of-the-art methods, techniques and equipment.

X
3

To be able to use techniques and tools for analyzing and designing industrial systems with a commitment to quality.

X
4

To be able to conduct basic research and write and publish articles in related conferences and journals.

X
5

To be able to carry out tests to measure the performance of industrial systems, analyze and interpret the subsequent results.

X
6

To be able to manage decision-making processes in industrial systems.

X
7

To have an aptitude for life-long learning; to be aware of new and upcoming applications in the field and to be able to learn them whenever necessary.

X
8

To have the scientific and ethical values within the society in the collection, interpretation, dissemination, containment and use of the necessary technologies related to Industrial Engineering.

X
9

To be able to design and implement studies based on theory, experiments and modeling; to be able to analyze and resolve the complex problems that arise in this process; to be able to prepare an original thesis that comply with Industrial Engineering criteria.

X
10

To be able to follow information about Industrial Engineering in a foreign language; to be able to present the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.

X

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