Industrial Engineering

Network Models(IND403)

Content
Course Code Course Name Semester Theory Practice Lab Credit ECTS
IND403 Network Models 7 3 0 0 3 4
Prerequisites IND371
Admission Requirements IND371
Language of Instruction
Course Type Elective
Course Level Bachelor Degree
Course Instructor(s) Ufuk BAHÇECİ ubahceci@gsu.edu.tr (Email)
Assistant
Objective The aim of this course is i) To ensure that the students learn the basic terminology related to graph theory, ii) To enable the student to evaluate how to model network flow problems that they may encounter in practice, iii) To enable the students to choose the appropriate method to solve a network flow model, and iv) To provide the students the ability to solve some special network flow problems encountered in practice. These problems, encountered in many areas such as production, logistics, supply chain, transportation, telecommunications, etc., can be modeled either directly or indirectly with network flow models, which are an important sub-branch of Operations Research. For this reason, the knowledge and skills to be acquired in this course will help graduate students both to solve the complex problems they will encounter in practice and to adapt to Industrial Engineering programs at the master's-doctoral level.
Content 1. Week: Course introduction
2. Week: Network models terminology
3. Week: Use of software for basic network models
4. Week: Minimum cost-flow problem
5. Week: Maximum flow problem
6. Week: Shortest path problem
7. Week: Assignment problem
8. Week: Midterm
9. Week: Minimum spanning tree problem
10. Week: Use of software for mixed-integer programming models
11. Week: Network simplex algorithm
12. Week: Traveling salesman problem
13. Week: Vehicle routing problem
14. Week: Project presentations
Course Learning Outcomes The student who successfully completes this course:
1. will learn the basic concepts of graph theory and network flows.
2. can mathematically model network flow problems that may be encountered in practice.
3. can determine the appropriate solution method for the basic network flow problems.
4. can solve some special network flow problems encountered in practice.
Teaching and Learning Methods Lecture; sample problems and applications; question-answer; individual study.
References 1. Ahuja, R.K., Magnanti, T.L., Orlin, J.L., “Network Flows: Theory, Algorithms, and Applications”, Prentice Hall, 1993.
2. Hillier, F.S., Lieberman, G.J., “Introduction to Operations Research”, McGraw-Hill, 2010.
3. Rosen, K.H., “Discrete Mathematics and Its Applications”, McGraw-Hill, 2007.
4. https://github.com/UfukBahceci/GraphUtilitiesPython
5. https://github.com/UfukBahceci/NetworkModelsLectureNotes
Print the course contents
Weekly Contents
Theory Topics
Week Weekly Contents
1 Course introduction
2 Network models terminology
3 Use of software for basic network models
4 Minimum cost-flow problem
5 Maximum flow problem
6 Shortest path problem
7 Assignment problem
8 Midterm
9 Minimum spanning tree problem
10 Use of software for mixed-integer programming models
11 Network simplex algorithm
12 Traveling salesman problem
13 Vehicle routing problem
14 Project presentations
Practice Topics
Week Weekly Contents
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Assessment System
Contribution to Overall Grade
  Number Contribution
Contribution of in-term studies to overall grade 2 60
Contribution of final exam to overall grade 1 40
Toplam 3 100
In-Term Studies
  Number Contribution
Assignments 0 0
Presentation 0 0
Midterm Examinations (including preparation) 1 30
Project 1 30
Laboratory 0 0
Other Applications 0 0
Quiz 0 0
Term Paper/ Project 0 0
Portfolio Study 0 0
Reports 0 0
Learning Diary 0 0
Thesis/ Project 0 0
Seminar 0 0
Other 0 0
Toplam 2 60
Relation of Proficiency
No Program Learning Outcomes Contribution
1 2 3 4 5
1 Knowledge and understanding of a wide range of basic sciences (math, physics, ...) and the main concepts of engineering X
2 Ability to combine the knowledge and skills to solve engineering problems and provide reliable solutions X
3 Ability to select and apply methods of analysis and modeling to ask, reformulate and solve the complex problems of industrial engineering X
4 Ability to conceptualize complex systems, processes or products under practical constraints to improve their performance, ability to use innovative methods of design X
5 Ability to design, select and apply methods and tools needed to solve problems related to the practice of industrial engineering, ability to use computer technology X
6 Ability to design experiments, collect and interpret data and analyze results
7 Ability to work independently, ability to participate in working groups and have a multidisciplinary team spirit X
8 Ability to communicate effectively, ability to speak at least two foreign languages X
9 Awareness of the need for continuous improvement of lifelong learning, ability to keep abreast of scientific and technological developments to use the tools of information management X
10 Awareness of professional and ethical responsibility
11 Knowledge of the concepts of professional life as "project management", "risk management" and "management of change"
12 Knowledge on entrepreneurship, innovation and sustainability
13 Understanding of the effects of Industrial Engineering applications on global and social health, environment and safety.
14 Knowledge of the problems of contemporary society
15 Knowledge of the legal implications of the practice of industrial engineering
ECTS
Activities Number Period Total Workload
Class Hours 14 3 42
Working Hours out of Class 14 2 28
Assignments 0 0 0
Presentation 0 0 0
Midterm Examinations (including preparation) 1 8 8
Project 1 8 8
Laboratory 0 0 0
Other Applications 0 0 0
Final Examinations (including preparation) 1 10 10
Quiz 0 0 0
Term Paper/ Project 0 0 0
Portfolio Study 0 0 0
Reports 0 0 0
Learning Diary 0 0 0
Thesis/ Project 0 0 0
Seminar 0 0 0
Other 0 0 0
Make-up 0 0 0
Total Workload 96
Total Workload / 25 3.84
Credits ECTS 4
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