FACULTY OF ENGINEERING

Department of Computer Engineering

IE 359 | Course Introduction and Application Information

Course Name
Network Optimization
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
IE 359
Fall/Spring
3
0
3
6

Prerequisites
  IE 252 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Service Course
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course Lecture / Presentation
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives Network flow problems form a subclass of linear programming problems with applications to transportation, logistics, manufacturing, computer science, project management, finance as well as a number of other domains. The aim of this course is to introduce the basic network problems and solution methods to the students.
Learning Outcomes The students who succeeded in this course;
  • Will be able to formulate a wide variety of industrial systems engineering applications as network flow problems
  • Will be able to identify well studied network flow problems like shortest path, minimum spanning tree and maximal flow
  • Will be able to build the mathematical models of network flow problems
  • Will be able to use various techniques to solve network optimization problems
  • Will be able to apply methods he/she learned to specially structured network optimization problems
Course Description Topics of this course include the shortest path problem, the maximum flow problem, the minimum cost flow problem, the multicommodity flow problem and other extensions of network flow problems.

 



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
1 Introduction, Notation and definitions Network Flows: Theory, Algorithms, and Applications, Chapters 1, 2
2 Shortest paths Network Flows: Theory, Algorithms, and Applications, Chapters 4
3 Shortest paths Network Flows: Theory, Algorithms, and Applications, Chapters 5
4 Maximum flows Network Flows: Theory, Algorithms, and Applications, Chapters 6-7-8
5 Maximum flows Network Flows: Theory, Algorithms, and Applications, Chapters 6-7-8
6 Minimum cost flows Network Flows: Theory, Algorithms, and Applications, Chapters 9-10-11
7 Minimum cost flows Network Flows: Theory, Algorithms, and Applications, Chapters 9-10-11
8 Minimum spanning trees Network Flows: Theory, Algorithms, and Applications, Chapters 13
9 Midterm
10 Assignments and matchings Network Flows: Theory, Algorithms, and Applications, Chapters 12-17
11 Transportation problem
12 Travelling salesman problem
13 Chinese postman problem, Vehicle routing problem
14 Project Presentations
15 Review of the Semester
16 Final

 

Course Notes/Textbooks

Instructor notes and lecture slides.

Suggested Readings/Materials

Ravindra K. Ahuja, Thomas L. Magnanti, James B. Orlin, Network Flows: Theory, Algorithms, and Applications, Prentice Hall. 

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
1
Laboratory / Application
Field Work
Quizzes / Studio Critiques
1
20
Portfolio
Homework / Assignments
Presentation / Jury
Project
1
15
Seminar / Workshop
Oral Exams
Midterm
1
30
Final Exam
1
35
Total

Weighting of Semester Activities on the Final Grade
4
70
Weighting of End-of-Semester Activities on the Final Grade
1
35
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
14
4
56
Field Work
0
Quizzes / Studio Critiques
1
15
15
Portfolio
0
Homework / Assignments
0
Presentation / Jury
0
Project
1
20
20
Seminar / Workshop
0
Oral Exam
0
Midterms
1
17
17
Final Exam
1
24
24
    Total
180

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

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

To have adequate knowledge in Mathematics, Science and Computer Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

2

To be able to identify, define, formulate, and solve complex Computer Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

3

To be able to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

4

To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in Computer Engineering applications; to be able to use information technologies effectively.

5

To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Computer Engineering research topics.

6

To be able to work efficiently in Computer Engineering disciplinary and multi-disciplinary teams; to be able to work individually.

7

To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions.

8

To have knowledge about global and social impact of Computer Engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of Computer Engineering solutions.

9

To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications.

10

To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

11

To be able to collect data in the area of Computer Engineering, and to be able to communicate with colleagues in a foreign language. ("European Language Portfolio Global Scale", Level B1)

12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Computer Engineering.

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

 


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