This course contains; A review of basic LP and introduction to Network Models,Transportation and transshipment models,Assignment models,Spanning tree Problems-Prim’s algorithm, Kruskal’s algorithm,Shortest Path Problems,Maximum Flow Problems Ford-Fulkerson Algorithm,Multicommondity Flow, and network synthesis problems,Introduction to Integer Programming,Formulating Integer Programming Problems,Formulating (Mixed) Integer Programming Problems,Solving Integer Programming Problems- branch and bound method and cutting
plane algorithm,Dynamic Programming,Nonlinear programming,Lagrange multipliers and Kuhn-Tucker conditions to solve constrained nonlinear
programming.
Dersin Öğrenme Kazanımları
Teaching Methods
Assessment Methods
Identifies transportation models.
12, 13, 14, 6, 8, 9
A, E, G
Identifies transshipment models.
12, 13, 14, 16, 6, 8, 9
A, G
Identifies assignment models.
12, 13, 14, 6, 8, 9
A, E
Identifies network models and solves them using appropriate algorithms.
12, 13, 14, 6, 8, 9
E, G
Defines integer programming models and solves them with appropriate algorithms.
12, 13, 14, 19, 6, 8, 9
A, E, G
Solves mathematical models and performs sensitivity analysis using mathematical programming software.
12, 13, 14, 16, 6, 8, 9
A, E, G
Solve mathematical models and perform sensitivity analysis using mathematical programming software.
12, 13, 14, 16, 6, 9
A, E, G
Teaching Methods:
12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 19: Brainstorming Technique, 6: Experiential Learning, 8: Flipped Classroom Learning, 9: Lecture Method
Assessment Methods:
A: Traditional Written Exam, E: Homework, G: Quiz
Course Outline
Order
Subjects
Preliminary Work
1
A review of basic LP and introduction to Network Models
Lecture Notes
2
Transportation and transshipment models
Lecture Notes
3
Assignment models
Lecture Notes
4
Spanning tree Problems-Prim’s algorithm, Kruskal’s algorithm
Lecture Notes
5
Shortest Path Problems
Lecture Notes
6
Maximum Flow Problems Ford-Fulkerson Algorithm
Lecture Notes
7
Multicommondity Flow, and network synthesis problems
Lecture Notes
8
Introduction to Integer Programming
Lecture Notes
9
Formulating Integer Programming Problems
Lecture Notes
10
Formulating (Mixed) Integer Programming Problems
Lecture Notes
11
Solving Integer Programming Problems- branch and bound method and cutting
plane algorithm
Lecture Notes
12
Dynamic Programming
Lecture Notes
13
Nonlinear programming
Lecture Notes
14
Lagrange multipliers and Kuhn-Tucker conditions to solve constrained nonlinear
programming
Lecture Notes
Resources
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
Develop and deepen knowledge in the same or in a different field to the proficiency level based on Bachelor level qualifications.
X
2
Conceive the interdisciplinary interaction which the field is related with.
X
3
Use of theoretical and practical knowledge within the field at a proficiency level and solve the problem faced related to the field by using research methods.
X
4
Interpret the knowledge about the field by integrating the information gathered from different disciplines and formulate new knowledge.
X
5
Independently conduct studies that require proficiency in the field.
X
6
Take responsibility and develop new strategic solutions as a team member in order to solve unexpected complex problems faced within the applications in the field.
X
7
Evaluate knowledge and skills acquired at proficiency level in the field with a critical approach and direct the learning.
X
8
Investigate, improve social connections and their conducting norms with a critical view and act to change them when necessary. Communicate with peers by using a foreign language at least at a level of European Language Portfolio B2 General Level.
X
9
Define the social and environmental aspects of engineering applications.
X
10
Audit the data gathering, interpretation, implementation and announcement stages by taking into consideration the cultural, scientific, and ethic values and teach these values.
X
Assessment Methods
Contribution Level
Absolute Evaluation
Rate of Midterm Exam to Success
50
Rate of Final Exam to Success
50
Total
100
ECTS / Workload Table
Activities
Number of
Duration(Hour)
Total Workload(Hour)
Course Hours
14
3
42
Guided Problem Solving
0
0
0
Resolution of Homework Problems and Submission as a Report
10
2
20
Term Project
0
0
0
Presentation of Project / Seminar
0
0
0
Quiz
8
12
96
Midterm Exam
1
32
32
General Exam
1
40
40
Performance Task, Maintenance Plan
0
0
0
Total Workload(Hour)
230
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(230/30)
8
ECTS of the course: 30 hours of work is counted as 1 ECTS credit.
Detail Informations of the Course
Course Description
Course
Code
Semester
T+P (Hour)
Credit
ECTS
NETWORK MODELS
-
Spring Semester
3+0
3
8
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of Course
Turkish
Course Level
Second Cycle (Master's Degree)
Course Type
Elective
Course Coordinator
Prof.Dr. Hakan TOZAN
Name of Lecturer(s)
Prof.Dr. Hakan TOZAN
Assistant(s)
Aim
Course Content
This course contains; A review of basic LP and introduction to Network Models,Transportation and transshipment models,Assignment models,Spanning tree Problems-Prim’s algorithm, Kruskal’s algorithm,Shortest Path Problems,Maximum Flow Problems Ford-Fulkerson Algorithm,Multicommondity Flow, and network synthesis problems,Introduction to Integer Programming,Formulating Integer Programming Problems,Formulating (Mixed) Integer Programming Problems,Solving Integer Programming Problems- branch and bound method and cutting
plane algorithm,Dynamic Programming,Nonlinear programming,Lagrange multipliers and Kuhn-Tucker conditions to solve constrained nonlinear
programming.
Dersin Öğrenme Kazanımları
Teaching Methods
Assessment Methods
Identifies transportation models.
12, 13, 14, 6, 8, 9
A, E, G
Identifies transshipment models.
12, 13, 14, 16, 6, 8, 9
A, G
Identifies assignment models.
12, 13, 14, 6, 8, 9
A, E
Identifies network models and solves them using appropriate algorithms.
12, 13, 14, 6, 8, 9
E, G
Defines integer programming models and solves them with appropriate algorithms.
12, 13, 14, 19, 6, 8, 9
A, E, G
Solves mathematical models and performs sensitivity analysis using mathematical programming software.
12, 13, 14, 16, 6, 8, 9
A, E, G
Solve mathematical models and perform sensitivity analysis using mathematical programming software.
12, 13, 14, 16, 6, 9
A, E, G
Teaching Methods:
12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 19: Brainstorming Technique, 6: Experiential Learning, 8: Flipped Classroom Learning, 9: Lecture Method
Assessment Methods:
A: Traditional Written Exam, E: Homework, G: Quiz
Course Outline
Order
Subjects
Preliminary Work
1
A review of basic LP and introduction to Network Models
Lecture Notes
2
Transportation and transshipment models
Lecture Notes
3
Assignment models
Lecture Notes
4
Spanning tree Problems-Prim’s algorithm, Kruskal’s algorithm
Lecture Notes
5
Shortest Path Problems
Lecture Notes
6
Maximum Flow Problems Ford-Fulkerson Algorithm
Lecture Notes
7
Multicommondity Flow, and network synthesis problems
Lecture Notes
8
Introduction to Integer Programming
Lecture Notes
9
Formulating Integer Programming Problems
Lecture Notes
10
Formulating (Mixed) Integer Programming Problems
Lecture Notes
11
Solving Integer Programming Problems- branch and bound method and cutting
plane algorithm
Lecture Notes
12
Dynamic Programming
Lecture Notes
13
Nonlinear programming
Lecture Notes
14
Lagrange multipliers and Kuhn-Tucker conditions to solve constrained nonlinear
programming
Lecture Notes
Resources
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
Develop and deepen knowledge in the same or in a different field to the proficiency level based on Bachelor level qualifications.
X
2
Conceive the interdisciplinary interaction which the field is related with.
X
3
Use of theoretical and practical knowledge within the field at a proficiency level and solve the problem faced related to the field by using research methods.
X
4
Interpret the knowledge about the field by integrating the information gathered from different disciplines and formulate new knowledge.
X
5
Independently conduct studies that require proficiency in the field.
X
6
Take responsibility and develop new strategic solutions as a team member in order to solve unexpected complex problems faced within the applications in the field.
X
7
Evaluate knowledge and skills acquired at proficiency level in the field with a critical approach and direct the learning.
X
8
Investigate, improve social connections and their conducting norms with a critical view and act to change them when necessary. Communicate with peers by using a foreign language at least at a level of European Language Portfolio B2 General Level.
X
9
Define the social and environmental aspects of engineering applications.
X
10
Audit the data gathering, interpretation, implementation and announcement stages by taking into consideration the cultural, scientific, and ethic values and teach these values.
