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TR

NETWORK ANALYSIS

Course
INDE301 - NETWORK ANALYSIS
Department
Industrial Engineering - English - Undergraduate
Course Type
Course
Status
Required
Language
English
Credit
3
ECTS
0
T+P+L
3 + 0 + 0
Course Coordinator(s)
-
Prerequisite
-
Keywords
-

Course Description

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NETWORK ANALYSIS

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

  1. 01 I. Learn basic information on graphs and networks and their structures
  2. 02 II. Model appropriate problems as a Minimum Spanning Tree Problem and solve them
  3. 03 II.III. Model appropriate problems as a Shortest Path Problem and solve them
  4. 04 IV. Model appropriate problems as a Maximum Flow Problem and solve them.
  5. 05 V. Model appropriate problems as a Minimum Cost Flow Problem and solve them.
  6. 06 VI. Ability to Plan and Manage Projects using network models.

Course Syllabus

Week Topic
Week 1 Introduction to graphs and networks.
Week 2 Problems that can be modeled as a minimum spanning tree network model. Solution algorithm for minimum spanning tree network. Examples.
Week 3 Problems that can be modeled as a Shortest Path Problem network model. Solution algorithm for minimum spanning tree network. Examples.
Week 4 Problems that can be modeled as a Maximum Flow Problem network model. Solution algorithm for minimum spanning tree network. Examples.
Week 5 Problems that can be modeled as a Minimum Cost Flow Problem network model.
Week 6 Solution algorithm for Minimum Cost Flow Problem network. Examples.
Week 7 WEEK FOR MIDTERM EXAMINATIONS
Week 8 Definition of project and project management.
Week 9 Defining the activities that make up the project and modelling activies as a network model. Finding the critical path using CPM.
Week 10 In case of the variability of the activity durations, use of PERT to calculate the critical path.
Week 11 Use of CPM/PERT results to prepare and control the project schedules
Week 12 Act,ons that may be taken in case there is a delay during the application of the project.
Week 13 -
Week 14 -
Week 15 -

Reference Books & Course Materials

  1. 01 Taha, H. A., "Operations Research", Prentice Hall.
  2. 02 Winston, W. L., "Operations Research", Thomson.
  3. 03 Ahuja, R.K., Magnanti, T.L., Orlin, J.B. (1993), "Network Flows", Prentice Hall.
  4. 04 Balkan, H. S., "Project Management using Network Analysis", class notes.

Learning Outcomes

  1. L01 I. Learn basic information on graphs and networks and their structures
  2. L02 II. Model appropriate problems as a Minimum Spanning Tree Problem and solve them
  3. L03 II.III. Model appropriate problems as a Shortest Path Problem and solve them
  4. L04 IV. Model appropriate problems as a Maximum Flow Problem and solve them.
  5. L05 V. Model appropriate problems as a Minimum Cost Flow Problem and solve them.
  6. L06 VI. Ability to Plan and Manage Projects using network models.

Program Outcomes

  1. P01 Knowledge of mathematics, natural sciences, basic engineering, computer-based computation, and topics specific to the relevant engineering discipline.
  2. P02 Ability to apply knowledge of mathematics, natural sciences, basic engineering, computer-based computation, and topics specific to the relevant engineering discipline to the solution of complex engineering problems.
  3. P03 Ability to define complex engineering problems by using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) related to the problem addressed.
  4. P04 Ability to formulate complex engineering problems using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) associated with the problem addressed.
  5. P05 Ability to analyse and solve complex engineering problems using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) associated with the problem addressed.
  6. P06 Ability to design creative solutions to complex engineering problems.
  7. P07 Ability to design complex systems, processes, devices, or products in a way that meets present and future needs while considering realistic constraints and conditions.
  8. P08 Ability to select and use appropriate techniques and resources—including estimation and modelling—for the analysis and solution of complex engineering problems, while being aware of their limitations.
  9. P09 Ability to select and use modern engineering and computational tools—including estimation and modelling—for the analysis and solution of complex engineering problems, while being aware of their limitations.
  10. P10 Ability to conduct literature research and use appropriate research methods for the investigation of complex engineering problems.
  11. P11 Ability to design experiments for the investigation of complex engineering problems.
  12. P12 Ability to conduct experiments, collect data, analyse results, and interpret findings for the investigation of complex engineering problems.
  13. P13 Knowledge of the impacts of engineering practices on society, health and safety, the economy, sustainability, and the environment within the framework of the United Nations Sustainable Development Goals (SDGs).
  14. P14 Awareness of the legal implications of engineering solutions within the framework of the United Nations Sustainable Development Goals (SDGs).
  15. P15 Knowledge of ethical responsibility and adherence to the principles of professional engineering conduct.
  16. P16 Awareness of acting impartially without discrimination in any matter and of being inclusive of diversity.
  17. P17 Ability to work effectively as an individual.
  18. P18 Ability to work effectively as a team member or leader in intra-disciplinary teams (face-to-face, remote, or hybrid).
  19. P19 Ability to work effectively as a team member or leader in multidisciplinary teams (face-to-face, remote, or hybrid).
  20. P20 Ability to communicate effectively in spoken form on technical matters, taking into account the diverse characteristics of the target audience (such as education, language, and profession).
  21. P21 Ability to communicate effectively in written form on technical matters, taking into account the diverse characteristics of the target audience (such as education, language, and profession).
  22. P22 Knowledge of professional practices such as project management and economic feasibility analysis.
  23. P23 Awareness of entrepreneurship and innovation.
  24. P24 Ability for independent and lifelong learning.
  25. P25 Ability to adapt to new and emerging technologies.
  26. P26 Lifelong learning ability that includes the capacity to think critically about technological changes.

Po-Lo Matrix

LO P01 P02 P03 P04 P05 P06 P07 P08 P09 P10 P11 P12 P13 P14 P15 P16 P17 P18 P19 P20 P21 P22 P23 P24 P25 P26 Average
L01 - - - - - - - - - - - - - - - - - - - - - - - - - - -
L02 - - - - - - - - - - - - - - - - - - - - - - - - - - -
L03 - - - - - - - - - - - - - - - - - - - - - - - - - - -
L04 - - - - - - - - - - - - - - - - - - - - - - - - - - -
L05 - - - - - - - - - - - - - - - - - - - - - - - - - - -
L06 - - - - - - - - - - - - - - - - - - - - - - - - - - -