- Main Page
- Information on the Institution
- General Description of the Institution
- Address of İzmir University of Economics
- Academic Authorities
- Academic Calendar
- Recognition of Prior Learning
- Recognition of Study Abroad
- List of Programs Offered
- General Admission Requirements
- General Registration Procedures
- ECTS Credit Allocation
- Grading
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- Internationalization
- Institutional ECTS Coordinator
- Departmental Erasmus Coordinators
- Degree Programs
- Mathematics
- Qualification Awarded
- Level of Qualification
- Specific Admission Requirements
- Qualification Requirements and Regulations
- Recognition of Prior Learning
- Profile of the Program
- Program Outcomes
- Course & Program Outcomes Matrix
- Occupational Profiles of Graduates
- Access to Further Studies
- Program Structure
- Course Structure Diagram with Credits
- Exam Regulations & Assessment & Grading
- Graduation Requirements
- Mode of Study
- Program Director (or Equivalent)
- Evaluation Questionnaires
- Courses
- General Information For Students
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COURSE INTRODUCTION AND APPLICATION INFORMATION
dm.ieu.edu.tr
| Course Name | |
| Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
|---|---|---|---|---|---|
| Fall/Spring |
| Prerequisites |
| ||||||||
| Course Language | |||||||||
| Course Type | Elective | ||||||||
| Course Level | - | ||||||||
| Mode of Delivery | - | ||||||||
| Teaching Methods and Techniques of the Course | |||||||||
| Course Coordinator | - | ||||||||
| Course Lecturer(s) | - | ||||||||
| Assistant(s) | - | ||||||||
| Course Objectives | |
| Learning Outcomes | The students who succeeded in this course;
|
| Course Description |
|
| Core Courses | |
| Major Area Courses | ||
| Supportive Courses | X | |
| Media and Managment Skills Courses | ||
| Transferable Skill Courses |
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
| Week | Subjects | Required Materials |
| 1 | Reminder for Optimization | Reading: Textbook (Michalewicz) introduction Ch 1 |
| 2 | Introduction to complexity and heuristics | Lecture notes/slides provided |
| 3 | Simulated Annealing | Lecture notes/ slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 8 |
| 4 | Particle Swarm Optimization | Lecture notes/slides provided |
| 5 | Genetic Algorithms and Evolutionary Strategies 1 | Lecture notes/slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 3 |
| 6 | Genetic Algorithms and Evolutionary Strategies 1 | Lecture notes/slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 3 |
| 7 | MIDTERM | |
| 8 | Ant Colony Optimization | Lecture notes/slides provided, Reading: Handbook of Metaheuristics Ch 9 |
| 9 | Tabu Search | Lecture notes/slides provided, Reading: Related textbook (Michalewicz) chapter 5 and Handbook of Metaheuristics Ch 2 |
| 10 | BAYRAM | |
| 11 | GRASP | Lecture notes/slides provided Handbook of Metaheuristics Ch 8 |
| 12 | Scatter Search | Lecture notes/slides provided Handbook of Metaheuristics Ch 1 |
| 13 | Local Search 1 | Lecture notes/slides provided Handbook of Metaheuristics Ch 11 |
| 14 | Local Search 2 Neighbourhoods, VNS | Lecture notes/slides provided Reading: Handbook of MetaheuristicsCh 6 |
| 15 | Review of Final | Lecture notes/slides provided |
| 16 | Review of the Semester |
| Course Notes/Textbooks | Textbook:Zbigniew Michalewicz, David B. Fogel “How to Solve It: Modern Heuristics |
| Suggested Readings/Materials | "Handbook of Metaheuristics" edt by: Glover F.,, Kochenberger G.A., Kluwer, 2003 and Lecture PowerPoint slides |
EVALUATION SYSTEM
| Semester Activities | Number | Weigthing |
| Participation | 5 | |
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques | ||
| Portfolio | ||
| Homework / Assignments | 5 | 20 |
| Presentation / Jury | ||
| Project | 1 | 35 |
| Seminar / Workshop | ||
| Oral Exam | ||
| Midterm | 1 | 20 |
| Final Exam | 1 | 20 |
| Total |
| Weighting of Semester Activities on the Final Grade | 80 | |
| Weighting of End-of-Semester Activities on the Final Grade | 20 | |
| 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 | 2 | |
| Field Work | |||
| Quizzes / Studio Critiques | |||
| Portfolio | |||
| Homework / Assignments | 5 | 2 | |
| Presentation / Jury | |||
| Project | 1 | 14 | |
| Seminar / Workshop | |||
| Oral Exam | |||
| Midterms | 1 | 8 | |
| Final Exams | 1 | 10 | |
| Total | 120 |
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
| # | Program Competencies/Outcomes | * Contribution Level | ||||
1 | 2 | 3 | 4 | 5 | ||
| 1 | To have a grasp of basic mathematics, applied mathematics and theories and applications of statistics. | |||||
| 2 | To be able to use theoretical and applied knowledge acquired in the advanced fields of mathematics and statistics, | |||||
| 3 | To be able to define and analyze problems and to find solutions based on scientific methods, | |||||
| 4 | To be able to apply mathematics and statistics in real life with interdisciplinary approach and to discover their potentials, | X | ||||
| 5 | To be able to acquire necessary information and to make modeling in any field that mathematics is used and to improve herself/himself, | X | ||||
| 6 | To be able to criticize and renew her/his own models and solutions, | X | ||||
| 7 | To be able to tell theoretical and technical information easily to both experts in detail and nonexperts in basic and comprehensible way, | |||||
| 8 | To be able to use international resources in English and in a second foreign language from the European Language Portfolio (at the level of B1) effectively and to keep knowledge up-to-date, to communicate comfortably with colleagues from Turkey and other countries, to follow periodic literature, | |||||
| 9 | To be familiar with computer programs used in the fields of mathematics and statistics and to be able to use at least one of them effectively at the European Computer Driving Licence Advanced Level, | |||||
| 10 | To be able to behave in accordance with social, scientific and ethical values in each step of the projects involved and to be able to introduce and apply projects in terms of civic engagement, | |||||
| 11 | To be able to evaluate all processes effectively and to have enough awareness about quality management by being conscious and having intellectual background in the universal sense, | |||||
| 12 | By having a way of abstract thinking, to be able to connect concrete events and to transfer solutions, to be able to design experiments, collect data, and analyze results by scientific methods and to interfere, | |||||
| 13 | To be able to continue lifelong learning by renewing the knowledge, the abilities and the compentencies which have been developed during the program, and being conscious about lifelong learning, | |||||
| 14 | To be able to adapt and transfer the knowledge gained in the areas of mathematics and statistics to the level of secondary school, | |||||
| 15 | To be able to conduct a research either as an individual or as a team member, and to be effective in each related step of the project, to take role in the decision process, to plan and manage the project by using time effectively. | |||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest