11111

COURSE INTRODUCTION AND APPLICATION INFORMATION


ce.cs.ieu.edu.tr

Course Name
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
Fall/Spring
Prerequisites
 ISE 204To succeed (To get a grade of at least DD)
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;
  • Will be able to understand combinatorial problems and their properties
  • Will be able to solve combinational problems using basic counting techniques
  • Will be able to identify famous combinatorial optimization problems
  • Will be able to use the mathematical techniques and heuristics related to famous combinatorial optimization problems
  • Will be able to apply simple algorithms involving combinatorial applications in graph theory, trees and searching, and networks
Course Description

 



Course Category

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 What is Combinatorics?
2 Introduction to Counting Reading the slides supplied by the instructor Inroduction to Basic Counting Rules
3 Basic counting rules I Reading the slides supplied by the instructor Basic Counting Rules
4 Basic counting rules II Reading the slides supplied by the instructor Basic Counting Rules
5 Basic counting rules III Reading the slides supplied by the instructor Basic Counting Rules
6 Recurrence relations I Reading the slides supplied by the instructor Recurrence relations
7 Recurrence relations II Reading the slides supplied by the instructor Recurrence relations
8 Midterm Exam
9 Graph Theory I Famous Problems in Combinatorial Optimization I Reading the slides supplied by the instructor Graph Theory
10 Graph Theory II Famous Problems in Combinatorial Optimization II Reading the slides supplied by the instructor Graph Theory
11 Graph Theory III Famous Problems in Combinatorial Optimization III Reading the slides supplied by the instructor Graph Theory
12 Graph Theory IV Famous Problems in Combinatorial Optimization IV Reading the slides supplied by the instructor Graph Theory
13 Computational Complexity, Analysis of algorithms Reading the slides supplied by the instructor Computational Complexity
14 Optimization Methods Famous Problems in Combinatorial Optimization V Reading the slides supplied by the instructor Optimization Methods
15 Midterm Exam
16 Review of the Semester  
Course Notes/Textbooks
Suggested Readings/Materials Introductory Combinatorics, R.A. Brualdi, Prentice Hall, NJ, 1999 Applied Combinatorics, F.S. Roberts, Prentice Hall, NJ, 1984 Applied Combinatorics, A. Tucker, John Wiley & Sons, NY, 1984 A Friendly Introduction to Graph Theory, F. Buckley and M. Lewinter, Prentice Hall, NJ, 2002 Discrete and Combinatorial Mathematics: An Applied Introduction, Fifth Edition. Ralph P. Grimaldi, Addison Wesley, 2003. Combinatorial Optimization: Algorithms and Complexity, Christos H. Papadimitriou and Kenneth Steiglitz, Dover Publications, 1998. Lecture handouts.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
1
10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
1
20
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm
2
70
Final Exam
Total

Weighting of Semester Activities on the Final Grade
100
Weighting of End-of-Semester Activities on the Final Grade
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
14
1
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
1
18
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms
2
20
Final Exams
    Total
120

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

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

Adequate knowledge in Mathematics, Science and Computer Engineering; ability to use theoretical and applied information in these areas to model and solve Computer Engineering problems

X
2

Ability to identify, define, formulate, and solve complex Computer Engineering problems; ability to select and apply proper analysis and modeling methods for this purpose

X
3

Ability to design a complex computer based system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose

X
4

Ability to devise, select, and use modern techniques and tools needed for Computer Engineering practice

X
5

Ability to design and conduct experiments, gather data, analyze and interpret results for investigating Computer Engineering problems

X
6

Ability to work efficiently in Computer Engineering disciplinary and multi-disciplinary teams; ability to work individually

7

Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of two foreign languages

8

Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself

9

Awareness of professional and ethical responsibility

10

Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development

11

Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of Computer Engineering solutions

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

 

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