COURSE INTRODUCTION AND APPLICATION INFORMATION

se.cs.ieu.edu.tr

Course Name

Code	Semester	Theory (hour/week)	Application/Lab (hour/week)	Local Credits	ECTS
	Fall/Spring

Prerequisites

ISE 204

To 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

Yrd. Doç. Dr. Zeynep SARGUT

Course Lecturer(s)

Yrd. Doç. Dr. Zeynep SARGUT

Assistant(s)

Course Objectives
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 use various techniques to solve network optimization problems
Course Description

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

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week	Subjects	Required Materials
1	Introduction, Notation and definitions	Network Flows: Theory, Algorithms, and Applications, Chapters 1, 2
2	Algorithm Design and Analysis	Network Flows: Theory, Algorithms, and Applications, Chapter 3
3	Shortest paths	Network Flows: Theory, Algorithms, and Applications, Chapter 4- 5
4	Shortest paths
5	Minimum spanning trees	Network Flows: Theory, Algorithms, and Applications, Chapter 13
6	maximum flows	6-7
7	maximum flows
8	minumum cost flows	9-11
9	minumum cost flows
10	minumum cost flows
11	multi-commodity flows	17
12	multi-commodity flows	17
13	Applications	19
14	Applications	other resources
15	Review
16	Review of the Semester

Course Notes/Textbooks	Ravindra K. Ahuja, Thomas L. Magnanti, James B. Orlin, Network Flows: Theory, Algorithms, and Applications, Prentice Hall. Instructor notes and lecture slides.
Suggested Readings/Materials

EVALUATION SYSTEM

Semester Activities	Number	Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques	5	50
Portfolio
Homework / Assignments
Presentation / Jury
Project	1	20
Seminar / Workshop
Oral Exam
Midterm
Final Exam	1	30
Total

Weighting of Semester Activities on the Final Grade		70
Weighting of End-of-Semester Activities on the Final Grade		30
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	5	4
Portfolio
Homework / Assignments
Presentation / Jury
Project	1	10
Seminar / Workshop
Oral Exam
Midterms
Final Exams	1	12
		Total	120

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	Program Competencies/Outcomes	* Contribution Level
#	Program Competencies/Outcomes	1	2	3	4	5
1	Be able to define problems in real life by identifying functional and nonfunctional requirements that the software is to execute
2	Be able to design and analyze software at component, subsystem, and software architecture level
3	Be able to develop software by coding, verifying, doing unit testing and debugging
4	Be able to verify software by testing its behaviour, execution conditions, and expected results
5	Be able to maintain software due to working environment changes, new user demands and the emergence of software errors that occur during operation
6	Be able to monitor and control changes in the software, the integration of software with other software systems, and plan to release software versions systematically
7	To have knowledge in the area of software requirements understanding, process planning, output specification, resource planning, risk management and quality planning
8	Be able to identify, evaluate, measure and manage changes in software development by applying software engineering processes
9	Be able to use various tools and methods to do the software requirements, design, development, testing and maintenance
10	To have knowledge of basic quality metrics, software life cycle processes, software quality, quality model characteristics, and be able to use them to develop, verify and test software
11	To have knowledge in other disciplines that have common boundaries with software engineering such as computer engineering, management, mathematics, project management, quality management, software ergonomics and systems engineering				X
12	Be able to grasp software engineering culture and concept of ethics, and have the basic information of applying them in the software engineering
13	Be able to use a foreign language to follow related field publications and communicate with colleagues				X

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