CLICK HERE FOR THE COURSE SYLLABUS (.pdf)


COURSE INTRODUCTION AND APPLICATION INFORMATION

 
Course Name
Code
Semester
Theory
(hour/week)
Application/Laboratory
(hour/week)
Local Credits
ECTS
Fuzzy Optimization
MATH 671
Fall/Spring
3
0
3
7.5

Prerequisites
None

Course Language
English
Course Type
Elective
Course Level
Third Cycle
Course Coordinator -
Course Lecturer(s)
Course Assistants -
Course Objectives Fuzzy Set Theory is the approach to solve the problems that cannot be solved by classical set theory or probability theory. In this course, Fuzzy Set Theory and the basis of fuzyy logic will be examined. It also describes, fuzzy logic applications such as fuzzy control and fuzzy decision making, disucced in the areas of optimization.
Course Learning Outcomes The students who succeeded in this course;
  • Be able to examine the Set Theory problems.
  • Be able to interpret the systems which include fuzzines within the scope of fuzzy set theory .
  • Be able to combine the information of decision theory and the information of fuzzy set theory.
  • Be able to improve the proof techniques of Fuzzy Set Theory.
  • Be able to solve problems that include uncertainty with using Fuzzy Set Theory.
Course Content The course covers basic concepts and applications of Fuzzy Set Theory.

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Fuzzy Sets Basic Definitions Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
2 Fuzzy Sets Basic Definitions Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
3 Fuzzy Measures and Fuzziness Measurements Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
4 Fuzzy Measures and Fuzziness Measurements Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
5 Fuzzy Relations and Fuzzy Graphics Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
6 Fuzzy Relations and Fuzzy Graphics Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
7 Possibility Theory, Probability Theory and Fuzzy Set Theory Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
8 Possibility Theory, Probability Theory and Fuzzy Set Theory Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
9 Fuzzy Logic Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
10 Midterm Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
11 Decision Makig in Fuzzy Environment Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
12 Decision Makig in Fuzzy Environment Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
13 Decision Makig in Fuzzy Environment Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
14 Decision Makig in Fuzzy Environment Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
15 Review Fuzzy Sets, Uncertainity, and Information by G.J. Klir and T.A. Folger, Prentice Hall, Inc.
16 Review of the Semester  

 

SOURCES

Course Notes / Textbooks Some chapters and exercises of the above books will be used.
References Fuzzy Logic with Engineering Applications by T.J. Ross, McGrawHill Book Company, 1995.

 

EVALUATION SYSTEM

Semester Requirements Number Percentage of Grade
Attendance/Participation
Laboratory
Application
Field Work
Special Course Internship (Work Placement)
Quizzes/Studio Critics
Homework Assignments
Presentation/Jury
1
30
Project
Seminar/Workshop
Midterms/Oral Exams
1
30
Final/Oral Exam
1
40
Total

PERCENTAGE OF SEMESTER WORK
60
PERCENTAGE OF FINAL WORK
40
Total

 

COURSE CATEGORY

Course Category

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

 

THE RELATIONSHIP BETWEEN COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS

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

To develop and deepen his/her knowledge on theories of mathematics and statistics and their applications in level of expertise, and to obtain unique definitions which bring innovations to the area, based on master level competencies,

X
2

To have the ability of original, independent and critical thinking in Mathematics and Statistics and to be able to develop theoretical concepts,

X
3

To have the ability of defining and verifying problems in Mathematics and Statistics,

X
4

With an interdisciplinary approach, to be able to apply theoretical and applied methods of mathematics and statistics in analyzing and solving new problems and to be able to discover his/her own potentials with respect to the application,

X
5

In nearly every fields that mathematics and statistics are used, to be able to execute, conclude and report a research, which requires expertise, independently,

X
6

To be able to evaluate and renew his/her abilities and knowledge acquired in the field of Applied Mathematics and Statistics with critical approach, and to be able to analyze, synthesize and evaluate complex thoughts in a critical way,

X
7

To be able to convey his/her analyses and methods in the field of Applied Mathematics and Statistics to the experts in a scientific way,

X
8

To be able to use national and international academic resources (English) efficiently, to update his/her knowledge, to communicate with his/her native and foreign colleagues easily, to follow the literature periodically, to contribute scientific meetings held in his/her own field and other fields systematically as written, oral and visual.

X
9

To be familiar with computer software commonly used in the fields of Applied Mathematics and Statistics and to be able to use at least two of them efficiently,

X
10

To contribute the transformation process of his/her own society into an information society and the sustainability of this process by introducing scientific, technological, social and cultural advances in the fields of Applied Mathematics and Statistics,

X
11

As having rich cultural background and social sensitivity with a global perspective, to be able to evaluate all processes efficiently, to be able to contribute the solutions of social, scientific, cultural and ethical problems and to support the development of these values,

X
12

As being competent in abstract thinking, to be able to connect abstract events to concrete events and to transfer solutions, to analyze results with scientific methods by designing experiment and collecting data and to interpret them,

X
13

To be able to produce strategies, policies and plans about systems and topics in which mathematics and statistics are used and to be able to interpret and develop results,

X
14

To be able to evaluate, argue and analyze prominent persons, events and phenomena, which play an important role in the development and combination of the fields of Mathematics and Statistics, within the perspective of the development of other fields of science,

X
15

In Applied Mathematics and Statistics, to be able to sustain scientific work as an individual or a group, to be effective in all phases of an independent work, to participate decision-making process and to make and execute necessary planning within an effective time schedule.

X

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

ECTS / WORKLOAD TABLE

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
15
3
Laboratory
Application
Special Course Internship (Work Placement)
Field Work
Study Hours Out of Class
15
6
Presentations / Seminar
Project
1
30
Homework Assignments
Quizzes
Midterms / Oral Exams
1
30
Final / Oral Exam
1
30
    Total Workload

CLICK HERE FOR THE COURSE SYLLABUS (.pdf)

 
 

İzmir Ekonomi Üniversitesi | Sakarya Caddesi No:156, 35330 Balçova - İZMİR Tel: +90 232 279 25 25 | webmaster@ieu.edu.tr | YBS 2010