11111

COURSE INTRODUCTION AND APPLICATION INFORMATION


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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 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, X
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,
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,

X
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.

X

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

 

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