NETWORK FLOWS and INTEGER PROGRAMMING

AIM

The 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.

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-1,Dynamic programming -2,Review.

1. 1

   Students build transportation models

   Taught by: Problem Solving Method, Case Study Method, Self Study Method, Experiential Learning, Flipped Classroom Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework, Quiz

2. 2

   Students build transshipment models.

   Taught by: Problem Solving Method, Case Study Method, Self Study Method, Experiential Learning, Flipped Classroom Learning, Lecture Method · Assessed by: Traditional Written Exam, Quiz

3. 3

   Students build assignment models.

   Taught by: Problem Solving Method, Case Study Method, Self Study Method, Experiential Learning, Flipped Classroom Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework

4. 4

   Students build network models using appropriate algorithms.

   Taught by: Problem Solving Method, Case Study Method, Self Study Method, Experiential Learning, Flipped Classroom Learning, Lecture Method · Assessed by: Homework, Quiz

5. 5

   Students solve integer programming models using appropriate algorithms

   Taught by: Problem Solving Method, Case Study Method, Self Study Method, Brainstorming Technique, Experiential Learning, Flipped Classroom Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework, Quiz

6. 6

   Students solve mathematical models using mathematical programming software.

   Taught by: Problem Solving Method, Case Study Method, Self Study Method, Question - Answer Technique, Experiential Learning, Flipped Classroom Learning, Lecture Method · Assessed by: Traditional Written Exam, Homework, Quiz

WEEKLY PLAN

1. WEEK 1

   A review of basic LP and introduction to Network Models

2. WEEK 2

   Transportation and transshipment models

3. WEEK 3

   Assignment models

4. WEEK 4

   Spanning tree Problems-Prim’s algorithm, Kruskal’s algorithm

5. WEEK 5

   Shortest Path Problems

6. WEEK 6

   Maximum Flow Problems Ford-Fulkerson Algorithm,

7. WEEK 7

   Multicommondity Flow, and network synthesis problems

8. WEEK 8

   Introduction to Integer Programming

9. WEEK 9

   Formulating Integer Programming Problems

10. WEEK 10

    Formulating (Mixed) Integer Programming Problems

11. WEEK 11

    Solving Integer Programming Problems- branch and bound method and cutting plane algorithm

12. WEEK 12

    Dynamic Programming-1

13. WEEK 13

    Dynamic programming -2

14. WEEK 14

    Review

ASSESSMENT

• Rate of Midterm Exam to Success30%
• Rate of Final Exam to Success70%

WORKLOAD

READING

• 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

TEACHING STAFF

• Lect.Dr. Esin TETİKCOORDINATOR
• Assoc.Prof. Yasin GÖÇGÜN