M.SC. in Computer Engineering (Without Thesis)

IE 515 | 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	-
National Occupation Classification	-
Course Coordinator	Yrd. Doç. Dr. Selin ÖZPEYNİRCİ
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

#	Content	PC Sub	* Contribution Level
#	Content	PC Sub	1	2	3	4	5
1	Learn the multi objective optimization methods
2	Identify the multi objective optimization method to pply a problem
3	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.

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	Learning Outcome
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	Weighting	LO 1	LO 2	LO 3
Participation	1	5
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments	4	20
Presentation / Jury	1	20
Project
Seminar / Workshop
Oral Exams
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
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	15	5	75
Field Work			0
Quizzes / Studio Critiques			0
Portfolio			0
Homework / Assignments	4	12	48
Presentation / Jury	1	10	10
Project			0
Seminar / Workshop			0
Oral Exam			0
Midterms	1	20	20
Final Exam	1	24	24
		Total	225

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	Accesses information in breadth and depth by conducting scientific research in Computer Engineering, evaluates, interprets and applies information.		-	-	-	X	-
2	Is well-informed about contemporary techniques and methods used in Computer Engineering and their limitations.		-	-	-	-	X
3	Uses scientific methods to complete and apply information from uncertain, limited or incomplete data, can combine and use information from different disciplines.		-	-	-	X	-
4	Is informed about new and upcoming applications in the field and learns them whenever necessary.		-	-	-	-	X
5	Defines and formulates problems related to Computer Engineering, develops methods to solve them and uses progressive methods in solutions.		-	-	-	-	X
6	Develops novel and/or original methods, designs complex systems or processes and develops progressive/alternative solutions in designs.		-	-	-	-	X
7	Designs and implements studies based on theory, experiments and modelling, analyses and resolves the complex problems that arise in this process.		-	-	-	X	-
8	Can work effectively in interdisciplinary teams as well as teams of the same discipline, can lead such teams and can develop approaches for resolving complex situations, can work independently and takes responsibility.		-	-	-	-	X
9	Engages in written and oral communication at least in Level B2 of the European Language Portfolio Global Scale.		-	-	X	-	-
10	Communicates the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.		-	-	X	-	-
11	Is knowledgeable about the social, environmental, health, security and law implications of Computer Engineering applications, knows their project management and business applications, and is aware of their limitations in Computer Engineering applications.		-	-	X	-	-
12	Highly regards scientific and ethical values in data collection, interpretation, communication and in every professional activity.		-	X	-	-	-