TÜRKÇE
ENGLISH
Information
| Unit | FACULTY OF ENGINEERING |
| INDUSTRIAL ENGINEERING PR. | |
| Code | ENM333 |
| Name | Mathematical Programming |
| Term | 2017-2018 Academic Year |
| Semester | 5. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 4 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Üniversite Dersi |
| Type | Normal |
| Label | C Compulsory |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. MELİK KOYUNCU |
| Course Instructor |
Prof. Dr. MELİK KOYUNCU
(Güz)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
To develop the operations researck skills and knowledge to delve into the mathematical modelling techniques
Course Content
To review the mathematical modelling techniques, Introduction to integer programming , The application area of integer programming, Solution methodology of integer programming ( branch and boun algorithm , additive algortihm) , Dynamic programming and its applications , The solution methodology of Dynamic progrramming , Introduction to Network models, The shortest path problem , Maximum flow problem and its applications, Minumum spanning tree problem and its applications, The network models related algorithm , Solving the some manufacturing problems by netwok models , Multiobjective optimization techniques, Introduction to goal programming , The solution methodology of goal programming
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Has sufficient background on topics related to mathematics, physical sciences and industrial engineering. | |
| PLO02 | - | Gains ability to use the acquired theoretical knowledge on basic sciences and industrial engineering for describing, formulating and solving an industrial engineering problem, and to choose appropriate analytical and modeling methods. | |
| PLO03 | - | Gains ability to analyze a service and/or manufacturing system or a process and describes, formulates and solves its problems . | |
| PLO04 | - | Gains ability to choose and apply methods and tools for industrial engineering applications. | |
| PLO05 | - | Can collect and analyze data required for industrial engineering problems ,develops and evaluates alternative solutions. | |
| PLO06 | - | Works efficiently and takes responsibility both individually and as a member of a multi-disciplinary team. | |
| PLO07 | - | Can access information and to search/use databases and other sources for information gathering. | |
| PLO08 | - | Appreciates life time learning; follows scientific and technological developments and renews himself/herself continuously. | |
| PLO09 | - | Can use computer software in industrial engineering along with information and communication technologies. | |
| PLO10 | - | Can use oral and written communication efficiently. | |
| PLO11 | - | Uses English skills to follow developments in industrial engineering and to communicate with people in his/her profession. | |
| PLO12 | - | Has a conscious understanding of professional and ethical responsibilities. | |
| PLO13 | - | Has a necessary consciousness on issues related to job safety and health, legal aspects of environment and engineering practice. | |
| PLO14 | - | Becomes competent on matters related to project management, entrepreneurship, innovation and has knowledge about current matters in industrial engineering. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | To review the mathematical modelling techniques | Standart lecture tools (Teaching on board and application) | |
| 2 | Introduction to integer programming | Standart lecture tools (Teaching on board and application) | |
| 3 | The application areas of integer programming | Standart lecture tools (Teaching on board and application) | |
| 4 | Solution methodology of integer programming ( branch and bound algorithm , additive algortihm) | Standart lecture tools (Teaching on board and application) | |
| 5 | Dynamic programming and its applications | Standart lecture tools (Teaching on board and application) | |
| 6 | The solution methodology of Dynamic programming | Standart lecture tools (Teaching on board and application) | |
| 7 | Midterm Exam | Classical Midternl Exam | |
| 8 | Introduction to Network models | Standart lecture tools (Teaching on board and application) | |
| 9 | The shortest path problem | Standart lecture tools (Teaching on board and application) | |
| 10 | Maximum flow problem and its applications | Standart lecture tools (Teaching on board and application) | |
| 11 | Minumum spanning tree problem and its applications | Standart lecture tools (Teaching on board and application) | |
| 12 | The network models related algorithm | Standart lecture tools (Teaching on board and application) | |
| 13 | Solving the some manufacturing problems by netwok models | Standart lecture tools (Teaching on board and application) | |
| 14 | Multiobjective optimization techniques | Standart lecture tools (Teaching on board and application) | |
| 15 | Introduction to goal programming | Standart lecture tools (Teaching on board and application) | |
| 16 | Final Exam | Classical Final Exam | |
| 17 | Final Exam | Classical Final Exam |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 100 | 40 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |