Department of Industrial 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	SPRING	3	0	3	6

Prerequisites	IE 252 To succeed (To get a grade of at least DD)
Course Language	English
Course Type	ELECTIVE_COURSE
Course Level	First Cycle
Mode of Delivery	Face to face
Teaching Methods and Techniques of the Course	Lecture / Presentation Problem solving
National Occupational Classification Code	-
Course Coordinator	Prof. Dr. Selin Özpeynirci
Course Lecturer(s)	Prof. Dr. Selin Özpeynirci
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;

Name	Description	PC Sub	* Contribution Level
Name	Description	PC Sub	1	2	3	4	5
LO1	Will be able to formulate a wide variety of industrial engineering applications as network flow problems	2		X
LO2	Will be able to use various techniques to solve shortest path problems	1.6		X
LO3	Will be able to use various techniques to solve maximum flow problems	1.6			X
LO4	Will be able to use various techniques to solve minimum cost flow problems	1.6			X
LO5	Will be able to use various techniques to solve minimum spanning tree and assignment problems	1.6			X
LO6	Will be able to identify and solve distribution and routing problems	4		X

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.

Related Sustainable Development Goals

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	Learning Outcome
1	Introduction, Notation and definitions	Lecture notes	LO1
2	Shortest path problem	Lecture notes	LO2
3	Shortest path problem	Lecture notes	LO2
4	Maximum flow problem	Lecture notes	LO3
5	Maximum flow problem	Lecture notes	LO3
6	Minimum cost flow problem	Lecture notes	LO4
7	Minimum cost flow problem	Lecture notes	LO4
8	Midterm exam		-
9	Minimum spanning trees, Assignments and matchings	Lecture notes	LO5
10	Transportation problem	Lecture notes	LO6
11	Travelling salesperson problem	Lecture notes	LO6
12	Chinese postman problem	Lecture notes	LO6
13	Vehicle routing problem	Lecture notes	LO6
14	Project Presentations		LO1
15	Review		-
16	Final exam		-

Course Notes/Textbooks	-
Suggested Readings/Materials	Lecture notes Ravindra K. Ahuja Thomas L. Magnanti James B. Orlin Network Flows: Theory Algorithms and Applications Prentice Hall. && Wayne L. Winston Operations Research. Applications and Algorithms Duxbury Press Belmont California 1994.

EVALUATION SYSTEM

Semester Activities	Number	Weighting	LO1	LO2	LO3	LO4	LO5	LO6
Quizzes / Studio Critiques	4	20		X	X	X	X	X
Project	1	15	X
Midterm	1	30	X	X	X	X
Final Exam	1	35					X	X
Total	7	100

ECTS / WORKLOAD TABLE

Semester Activities	Number	Duration (Hours)	Workload
Participation	-	-	-
Theoretical Course Hours	16	3	48
Laboratory / Application Hours	-	-	-
Study Hours Out of Class	14	4	56
Field Work	-	-	-
Quizzes / Studio Critiques	4	4	16
Portfolio	-	-	-
Homework / Assignments	-	-	-
Presentation / Jury	-	-	-
Project	1	20	20
Seminar / Workshop	-	-	-
Oral Exams	-	-	-
Midterms	1	17	17
Final Exam	1	23	23
		Total	180

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#	PC Sub	Program Competencies/Outcomes	* Contribution Level
#	PC Sub	Program Competencies/Outcomes	1	2	3	4	5
1	Engineering Knowledge: Knowledge of mathematics, science, basic engineering, computation, and related engineering discipline-specific topics; the ability to apply this knowledge to solve complex engineering problems.
	1	Mathematics
	2	Science
	3	Basic Engineering
	4	Computation
	5	Related engineering discipline-specific topics
	6	The ability to apply this knowledge to solve complex engineering problems		LO2	LO3 LO4 LO5
2	Problem Analysis: Ability to identify, formulate and analyze complex engineering problems using basic knowledge of science, mathematics and engineering, and considering the UN Sustainable Development Goals relevant to the problem being addressed.			LO1
3	Engineering Design: The ability to devise creative solutions to complex engineering problems; the ability to design complex systems, processes, devices or products to meet current and future needs, considering realistic constraints and conditions.
	1	Ability to design creative solutions to complex engineering problems
	2	Ability to design complex systems, processes, devices or products to meet current and future needs, considering realistic constraints and conditions
4	Use of Techniques and Tools: Ability to select and use appropriate techniques, resources, and modern engineering and computing tools, including estimation and modeling, for the analysis and solution of complex engineering problems, while recognizing their limitations.			LO6
5	Research and Investigation: Ability to use research methods to investigate complex engineering problems, including literature research, designing and conducting experiments, collecting data, and analyzing and interpreting results.
	1	Literature research for the study of complex engineering problems
	2	Designing experiments
	3	Ability to use research methods, including conducting experiments, collecting data. analyzing and interpreting results
6	Global Impact of Engineering Practices: Knowledge of the impacts of engineering practices on society, health and safety, economy, sustainability, and the environment, within the context of the UN Sustainable Development Goals; awareness of the legal implications of engineering solutions.
	1	Knowledge of the impacts of engineering practices on society, health and safety, economy, sustainability, and the environment, within the context of the UN Sustainable Development Goals
	2	Awareness of the legal implications of engineering solutions
7	Ethical Behavior: Acting in accordance with the principles of the engineering profession, knowledge about ethical responsibility; awareness of being impartial, without discrimination, and being inclusive of diversity.
	1	Acting in accordance with the principles of the engineering profession, knowledge about ethical responsibility ethical responsibility
	2	Awareness of being impartial and inclusive of diversity, without discriminating on any subject
8	Individual and Teamwork: Ability to work effectively, individually and as a team member or leader on interdisciplinary and multidisciplinary teams (face-to-face, remote or hybrid).
	1	Ability to work individually and within the discipline
	2	Ability to work effectively as a team member or leader in multidisciplinary teams (face-to-face, remote or hybrid)
9	Verbal and Written Communication: Taking into account the various differences of the target audience (such as education, language, profession) on technical issues.
	1	Ability to communicate verbally
	2	Ability to communicate effectively in writing
10	Project Management: Knowledge of business practices such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation.
	1	Knowledge of business practices such as project management and economic feasibility analysis
	2	Awareness of entrepreneurship and innovation
11	Lifelong Learning: Lifelong learning skills that include being able to learn independently and continuously, adapting to new and developing technologies, and thinking questioningly about technological changes.