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Course Detail

Course Description

CourseCodeSemesterT+P (Hour)CreditECTS
NETWORK FLOWS and INTEGER PROGRAMMING-Fall Semester3+036
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of CourseEnglish
Course LevelFirst Cycle (Bachelor's Degree)
Course TypeRequired
Course CoordinatorAssoc.Prof. Yasin GÖÇGÜN
Name of Lecturer(s)Prof.Dr. Hakan TOZAN
Assistant(s)
AimThe students who succeeded the course will be able to identify and formulate Network problems; be able to identify and formulate Integer Programming problems; acquire basic skills to formulate and build integer and nonlinear programming models, and select and implement appropriate solution techniques.
Course ContentThis 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-1,Dynamic programming -2,Review.
Dersin Öğrenme KazanımlarıTeaching MethodsAssessment Methods
Students build transportation models12, 13, 14, 6, 8, 9A, E, G
Students build transshipment models.12, 13, 14, 6, 8, 9A, G
Students build assignment models.12, 13, 14, 6, 8, 9A, E
Students build network models using appropriate algorithms.12, 13, 14, 6, 8, 9E, G
Students solve integer programming models using appropriate algorithms12, 13, 14, 19, 6, 8, 9A, E, G
Students solve mathematical models using mathematical programming software.12, 13, 14, 16, 6, 8, 9A, 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

OrderSubjectsPreliminary Work
1A review of basic LP and introduction to Network Models
2 Transportation and transshipment models
3Assignment models
4Spanning tree Problems-Prim’s algorithm, Kruskal’s algorithm
5Shortest Path Problems
6Maximum Flow Problems Ford-Fulkerson Algorithm,
7Multicommondity Flow, and network synthesis problems
8Introduction to Integer Programming
9Formulating Integer Programming Problems
10Formulating (Mixed) Integer Programming Problems
11Solving Integer Programming Problems- branch and bound method and cutting plane algorithm
12Dynamic Programming-1
13Dynamic programming -2
14Review
Resources
Taha, Hamdy A., Operations Research, 8th edition, 2007. ISBN: 0131360140; Bazaraa M.S., Jarvis J.J., Sherali H.D., Linear Programming and Network Flows, 3 th Edition, ISBN 978-0-470-46272-0
Ahuja R.K., Magnanti T.L., Orlin B.J.; Network Flows Theory, Algorithms, and Applications, Prentice Hall. ISBN-13: 978-0136175490 Winston, Wayne L., Operations Research: Applications and Algorithms, 4th edition, 2003. ISBN-13: 978-0534380588

Course Contribution to Program Qualifications

Course Contribution to Program Qualifications
NoProgram QualificationContribution Level
12345
1
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems.
X
2
Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
X
3
Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose.
X
4
Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively.
X
5
Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.
X
6
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
X
7
Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
X
8
Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
X
9
Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices.
X
10
Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development.
X
11
Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.
X

Assessment Methods

Contribution LevelAbsolute Evaluation
Rate of Midterm Exam to Success 30
Rate of Final Exam to Success 70
Total 100
ECTS / Workload Table
ActivitiesNumber ofDuration(Hour)Total Workload(Hour)
Course Hours14342
Guided Problem Solving000
Resolution of Homework Problems and Submission as a Report14114
Term Project000
Presentation of Project / Seminar000
Quiz51050
Midterm Exam13030
General Exam14444
Performance Task, Maintenance Plan000
Total Workload(Hour)180
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(180/30)6
ECTS of the course: 30 hours of work is counted as 1 ECTS credit.

Detail Informations of the Course

Course Description

CourseCodeSemesterT+P (Hour)CreditECTS
NETWORK FLOWS and INTEGER PROGRAMMING-Fall Semester3+036
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of CourseEnglish
Course LevelFirst Cycle (Bachelor's Degree)
Course TypeRequired
Course CoordinatorAssoc.Prof. Yasin GÖÇGÜN
Name of Lecturer(s)Prof.Dr. Hakan TOZAN
Assistant(s)
AimThe students who succeeded the course will be able to identify and formulate Network problems; be able to identify and formulate Integer Programming problems; acquire basic skills to formulate and build integer and nonlinear programming models, and select and implement appropriate solution techniques.
Course ContentThis 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-1,Dynamic programming -2,Review.
Dersin Öğrenme KazanımlarıTeaching MethodsAssessment Methods
Students build transportation models12, 13, 14, 6, 8, 9A, E, G
Students build transshipment models.12, 13, 14, 6, 8, 9A, G
Students build assignment models.12, 13, 14, 6, 8, 9A, E
Students build network models using appropriate algorithms.12, 13, 14, 6, 8, 9E, G
Students solve integer programming models using appropriate algorithms12, 13, 14, 19, 6, 8, 9A, E, G
Students solve mathematical models using mathematical programming software.12, 13, 14, 16, 6, 8, 9A, 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

OrderSubjectsPreliminary Work
1A review of basic LP and introduction to Network Models
2 Transportation and transshipment models
3Assignment models
4Spanning tree Problems-Prim’s algorithm, Kruskal’s algorithm
5Shortest Path Problems
6Maximum Flow Problems Ford-Fulkerson Algorithm,
7Multicommondity Flow, and network synthesis problems
8Introduction to Integer Programming
9Formulating Integer Programming Problems
10Formulating (Mixed) Integer Programming Problems
11Solving Integer Programming Problems- branch and bound method and cutting plane algorithm
12Dynamic Programming-1
13Dynamic programming -2
14Review
Resources
Taha, Hamdy A., Operations Research, 8th edition, 2007. ISBN: 0131360140; Bazaraa M.S., Jarvis J.J., Sherali H.D., Linear Programming and Network Flows, 3 th Edition, ISBN 978-0-470-46272-0
Ahuja R.K., Magnanti T.L., Orlin B.J.; Network Flows Theory, Algorithms, and Applications, Prentice Hall. ISBN-13: 978-0136175490 Winston, Wayne L., Operations Research: Applications and Algorithms, 4th edition, 2003. ISBN-13: 978-0534380588

Course Contribution to Program Qualifications

Course Contribution to Program Qualifications
NoProgram QualificationContribution Level
12345
1
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems.
X
2
Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
X
3
Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose.
X
4
Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively.
X
5
Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.
X
6
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
X
7
Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
X
8
Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
X
9
Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices.
X
10
Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development.
X
11
Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.
X

Assessment Methods

Contribution LevelAbsolute Evaluation
Rate of Midterm Exam to Success 30
Rate of Final Exam to Success 70
Total 100

Numerical Data

Student Success

Ekleme Tarihi: 09/10/2023 - 10:42Son Güncelleme Tarihi: 09/10/2023 - 10:43