NETWORK MODELS

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.

1. 1

   Identifies 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

   Identifies transshipment models.

   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, Quiz

3. 3

   Identifies 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

   Identifies network models and solves them 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

   Defines integer programming models and solves them with 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

   Solves mathematical models and performs sensitivity analysis 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

7. 7

   Solve mathematical models and perform sensitivity analysis using mathematical programming software.

   Taught by: Problem Solving Method, Case Study Method, Self Study Method, Question - Answer Technique, Experiential 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

   Preparation: Lecture Notes

2. WEEK 2

   Transportation and transshipment models

   Preparation: Lecture Notes

3. WEEK 3

   Assignment models

   Preparation: Lecture Notes

4. WEEK 4

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

   Preparation: Lecture Notes

5. WEEK 5

   Shortest Path Problems

   Preparation: Lecture Notes

6. WEEK 6

   Maximum Flow Problems Ford-Fulkerson Algorithm

   Preparation: Lecture Notes

7. WEEK 7

   Multicommondity Flow, and network synthesis problems

   Preparation: Lecture Notes

8. WEEK 8

   Introduction to Integer Programming

   Preparation: Lecture Notes

9. WEEK 9

   Formulating Integer Programming Problems

   Preparation: Lecture Notes

10. WEEK 10

    Formulating (Mixed) Integer Programming Problems

    Preparation: Lecture Notes

11. WEEK 11

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

    Preparation: Lecture Notes

12. WEEK 12

    Dynamic Programming

    Preparation: Lecture Notes

13. WEEK 13

    Nonlinear programming

    Preparation: Lecture Notes

14. WEEK 14

    Lagrange multipliers and Kuhn-Tucker conditions to solve constrained nonlinear programming

    Preparation: Lecture Notes

ASSESSMENT

• Rate of Midterm Exam to Success50%
• Rate of Final Exam to Success50%

WORKLOAD

TEACHING STAFF

• Assoc.Prof. Yasin GÖÇGÜNCOORDINATOR
• Assist.Prof. Rüçhan Melisa DENİZ ÖZGEN