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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| INDUSTRIAL ENGINEERING (MASTER) (WITH THESIS) | |
| Code | EM511 |
| Name | Mathematical Modelling and Optimization |
| Term | 2019-2020 Academic Year |
| Term | Fall |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. ALİ KOKANGÜL |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The aim of this course is to provide detailed information on mathematical programming techniques and to help students gain ability to apply these techniques using LINDO package program.
Course Content
Mathematical models used in optimization problems, numerical methods for unconstrained optimization problems with one variable, numerical methods for constrained optimization problems with one variable, numerical methods for unconstrained optimization problems with multi-variable, numerical methods for constrained optimization problems with multi-variable, applications of mathematical models,project presentation.
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | To be able to set a mathematical model of any real life problem |
| LO02 | Choosing the most appropriate mathematical modeling approach |
| LO03 | Testing the validity of the model |
| LO04 | To gain the ability of using the solution derivation, application and LINGO package program |
| LO05 | To derive the solution in the model's computer package program |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Understands, interprets and applies knowledge in his/her field domain both in-depth and in-breadth by doing scientific research in industrial engineering. | 5 |
| PLO02 | - | Acquires comprehensive knowledge about methods and tools of industrial engineering and their limitations. | 4 |
| PLO03 | - | Designs and performs analytical modeling and experimental research and analyze/solves complex matters emerged in this process. | 5 |
| PLO04 | - | Completes and applies the knowledge by using scarce and limited resources in a scientific way and integrates the knowledge into various disciplines. | 4 |
| PLO05 | - | Keeps up with the recent changes and applications in the field of Industrial Engineering and examines and learns these innovations when necessary. | 5 |
| PLO06 | - | Has the ability to propose new and/or original ideas and methods, develops innovative solutions for designing systems, components or processes. | 4 |
| PLO07 | - | Designs Industrial Engineering problems, develops innovative methods to solve the problems and applies them. | 5 |
| PLO08 | - | Works in multi-disciplinary teams and takes a leading role and responsibility. | 4 |
| PLO09 | - | Identifies, gathers and uses necessary information and data. | 4 |
| PLO10 | - | Follows, studies and learns new and developing applications of industrial engineering. | 5 |
| PLO11 | - | Uses a foreign language in verbal and written communication at least B2 level of European Language Portfolio. | 2 |
| PLO12 | - | Presents his/her research findings systematically and clearly in oral and written forms in national and international platforms. | 3 |
| PLO13 | - | Understands social and environmental implications of engineering practice. | 5 |
| PLO14 | - | Considers social, scientific and ethical values in the process of data collection, interpretation and announcement of the findings. | 5 |
| PLO15 | - | Works in multi-disciplinary teams, take a leading role and responsibility and develop solutions for complex problems. | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to mathematical programming | Preliminary research on the subject and investigation of current applications | |
| 2 | Mathematical models used in optimization problems | Preliminary research on the subject and investigation of current applications | |
| 3 | Unconstrained mathematical modeling techniques | Preliminary research on the subject and investigation of current applications | |
| 4 | Constrained mathematical modeling techniques | Preliminary research on the subject and investigation of current applications | |
| 5 | Numerical methods for unconstrained optimization problems with one variable | Preliminary research on the subject and investigation of current applications | |
| 6 | Numerical methods for constrained optimization problems with one variable | Preliminary research on the subject and investigation of current applications | |
| 7 | Numerical methods for unconstrained optimization problems with multi-variable | Preliminary research on the subject and investigation of current applications | |
| 8 | Mid-Term Exam | Preparation for the exam | |
| 9 | Numerical methods for unconstrained optimization problems with multi-variable | Preliminary research on the subject and investigation of current applications | |
| 10 | Numerical methods for constrained optimization problems with multi-variable | Preliminary research on the subject and investigation of current applications | |
| 11 | Numerical methods for constrained optimization problems with multi-variable | Preliminary research on the subject and investigation of current applications | |
| 12 | Applications of mathematical models | Preliminary research on the subject and investigation of current applications | |
| 13 | Applications of mathematical models | Preliminary research on the subject and investigation of current applications | |
| 14 | Project presentation | Preliminary research on the subject and investigation of current applications | |
| 15 | Project presentation | Preliminary research on the subject and investigation of current applications | |
| 16 | Term Exams | Preparation for the exam | |
| 17 | Term Exams | Preparation for the exam |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||