Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| MODELING and OPTIMIZATION | SSMY1163590 | Fall 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 | Assoc.Prof. Yasin GÖÇGÜN |
| Name of Lecturer(s) | Prof.Dr. Hakan TOZAN |
| Assistant(s) | |
| Aim | |
| Course Content | This course contains; Introduction to Model Building,Basic Linear Algebra,Introduction to Linear Programming,Convex Sets and Functions, Extreme Points and Optimality, Graphical Solution,Graphical Sensitivity Analysis and Computer Based Solutions,Simplex Algorithm ,Simplex Algorithm,Simplex Algorithm: Artificial Starting Solutions,Simplex Algorithm: Artificial Starting Solutions and Special Cases in Simplex,Special Simplex Implementations: Revised simplex, Karus-Kuhn-Tucker Optimality Conditions,Duality and Sensitivity: Dual Simplex,Duality and Sensitivity: Dual Simplex,Transportatio and Assignment Problems,Transportatio and Assignment Problems. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| 12, 13, 14, 16, 6, 8, 9 | A, E, G, H | |
| 12, 13, 14, 16, 6, 8, 9 | A, E, H | |
| 12, 14, 16, 21, 6, 8, 9 | A, G | |
| 12, 14, 16, 8, 9 | G | |
| 12, 14, 16, 9 | A | |
| 12, 14, 16, 6, 9 | A |
| Teaching Methods: | 12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 21: Simulation Technique, 6: Experiential Learning, 8: Flipped Classroom Learning, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam, E: Homework, G: Quiz, H: Performance Task |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Model Building | Week 1 presentation notes. |
| 2 | Basic Linear Algebra | Week 2 presentation notes. |
| 3 | Introduction to Linear Programming | Week 3 presentation notes. |
| 4 | Convex Sets and Functions, Extreme Points and Optimality, Graphical Solution | Week 4 presentation notes. |
| 5 | Graphical Sensitivity Analysis and Computer Based Solutions | Week 5 presentation notes. |
| 6 | Simplex Algorithm | Week 6 presentation notes. |
| 7 | Simplex Algorithm | Week 7 presentation notes (week 6 continued). |
| 8 | Simplex Algorithm: Artificial Starting Solutions | Week 8 presentation notes. |
| 9 | Simplex Algorithm: Artificial Starting Solutions and Special Cases in Simplex | Week 9 presentation notes (week 8 continued). |
| 10 | Special Simplex Implementations: Revised simplex, Karus-Kuhn-Tucker Optimality Conditions | Week 10 presentation notes. |
| 11 | Duality and Sensitivity: Dual Simplex | Week 11 presentation notes - part 1. |
| 12 | Duality and Sensitivity: Dual Simplex | Week 11 presentation notes - part 2. |
| 13 | Transportatio and Assignment Problems | Week 13 presentation notes. |
| 14 | Transportatio and Assignment Problems | Week 13 presentation 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 | 9 | 12 | 108 | |||
| Term Project | 3 | 10 | 30 | |||
| Presentation of Project / Seminar | 0 | 0 | 0 | |||
| Quiz | 0 | 0 | 0 | |||
| Midterm Exam | 1 | 25 | 25 | |||
| General Exam | 1 | 40 | 40 | |||
| Performance Task, Maintenance Plan | 0 | 0 | 0 | |||
| Total Workload(Hour) | 245 | |||||
| Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(245/30) | 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 |
|---|---|---|---|---|---|
| MODELING and OPTIMIZATION | SSMY1163590 | Fall 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 | Assoc.Prof. Yasin GÖÇGÜN |
| Name of Lecturer(s) | Prof.Dr. Hakan TOZAN |
| Assistant(s) | |
| Aim | |
| Course Content | This course contains; Introduction to Model Building,Basic Linear Algebra,Introduction to Linear Programming,Convex Sets and Functions, Extreme Points and Optimality, Graphical Solution,Graphical Sensitivity Analysis and Computer Based Solutions,Simplex Algorithm ,Simplex Algorithm,Simplex Algorithm: Artificial Starting Solutions,Simplex Algorithm: Artificial Starting Solutions and Special Cases in Simplex,Special Simplex Implementations: Revised simplex, Karus-Kuhn-Tucker Optimality Conditions,Duality and Sensitivity: Dual Simplex,Duality and Sensitivity: Dual Simplex,Transportatio and Assignment Problems,Transportatio and Assignment Problems. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| 12, 13, 14, 16, 6, 8, 9 | A, E, G, H | |
| 12, 13, 14, 16, 6, 8, 9 | A, E, H | |
| 12, 14, 16, 21, 6, 8, 9 | A, G | |
| 12, 14, 16, 8, 9 | G | |
| 12, 14, 16, 9 | A | |
| 12, 14, 16, 6, 9 | A |
| Teaching Methods: | 12: Problem Solving Method, 13: Case Study Method, 14: Self Study Method, 16: Question - Answer Technique, 21: Simulation Technique, 6: Experiential Learning, 8: Flipped Classroom Learning, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam, E: Homework, G: Quiz, H: Performance Task |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Model Building | Week 1 presentation notes. |
| 2 | Basic Linear Algebra | Week 2 presentation notes. |
| 3 | Introduction to Linear Programming | Week 3 presentation notes. |
| 4 | Convex Sets and Functions, Extreme Points and Optimality, Graphical Solution | Week 4 presentation notes. |
| 5 | Graphical Sensitivity Analysis and Computer Based Solutions | Week 5 presentation notes. |
| 6 | Simplex Algorithm | Week 6 presentation notes. |
| 7 | Simplex Algorithm | Week 7 presentation notes (week 6 continued). |
| 8 | Simplex Algorithm: Artificial Starting Solutions | Week 8 presentation notes. |
| 9 | Simplex Algorithm: Artificial Starting Solutions and Special Cases in Simplex | Week 9 presentation notes (week 8 continued). |
| 10 | Special Simplex Implementations: Revised simplex, Karus-Kuhn-Tucker Optimality Conditions | Week 10 presentation notes. |
| 11 | Duality and Sensitivity: Dual Simplex | Week 11 presentation notes - part 1. |
| 12 | Duality and Sensitivity: Dual Simplex | Week 11 presentation notes - part 2. |
| 13 | Transportatio and Assignment Problems | Week 13 presentation notes. |
| 14 | Transportatio and Assignment Problems | Week 13 presentation 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 | |