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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| INDUSTRIAL ENGINEERING (PhD) | |
| Code | EM540 |
| Name | Nonlinear Programming |
| Term | 2019-2020 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Doktora 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
Mathematical modeling of the problems in real life, selection of the most suitable method for the modeled problem, solution derivation, transfer of the information necessary for the testing and implementation of the validity of the solution.
Course Content
Local and global optimization, Optimality conditions, Necessary and sufficient conditions for optimality, Unconstrained optimization, Constrained Optimization, Necessary and sufficient conditions for constrained optimization, Quadratic programming, Lagrangean methods, Convex analysis and convex programming, Multi-objective optimization methods, Computer implementation.
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Improving analytical thinking ability |
| LO02 | Model problems in real life |
| LO03 | To be able to make sensitivity analysis |
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. | 5 |
| PLO05 | - | Keeps up with the recent changes and applications in the field of Industrial Engineering and examines and learns these innovations when necessary. | 4 |
| PLO06 | - | Has the ability to propose new and/or original ideas and methods, develops innovative solutions for designing systems, components or processes. | 3 |
| PLO07 | - | Develops original definitions that will provide innovation to the field at the level of expertise for current and advanced information in the field based on graduate qualifications. | 4 |
| PLO08 | - | Designs Industrial Engineering problems, develops innovative methods to solve the problems and applies them. | 5 |
| PLO09 | - | Works in multi-disciplinary teams and takes a leading role and responsibility. | 4 |
| PLO10 | - | Identifies, gathers and uses necessary information and data. | 5 |
| PLO11 | - | Follows, studies and learns new and developing applications of industrial engineering. | 3 |
| PLO12 | - | Uses a foreign language in verbal and written communication at least B2 level of European Language Portfolio. | 3 |
| PLO13 | - | Presents his/her research findings systematically and clearly in oral and written forms in national and international platforms. | 4 |
| PLO14 | - | Understands social and environmental implications of engineering practice. | 4 |
| PLO15 | - | Considers social, scientific and ethical values in the process of data collection, interpretation and announcement of the findings. | 5 |
| PLO16 | - | 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 | Local and global optimization | Preliminary research on the subject and investigation of current applications | |
| 2 | Optimality conditions | Preliminary research on the subject and investigation of current applications | |
| 3 | Necessary and sufficient conditions for optimality | Preliminary research on the subject and investigation of current applications | |
| 4 | Unconstrained optimization-I | Preliminary research on the subject and investigation of current applications | |
| 5 | Unconstrained optimization-II | Preliminary research on the subject and investigation of current applications | |
| 6 | Constrained Optimization-I | Preliminary research on the subject and investigation of current applications | |
| 7 | Constrained Optimization-II | Preliminary research on the subject and investigation of current applications | |
| 8 | Mid-Term Exam | Preparation for the exam | |
| 9 | Necessary and sufficient conditions for constrained optimization | Preliminary research on the subject and investigation of current applications | |
| 10 | Quadratic programming | Preliminary research on the subject and investigation of current applications | |
| 11 | Lagrangian methods | Preliminary research on the subject and investigation of current applications | |
| 12 | Convex analysis and convex programming | Preliminary research on the subject and investigation of current applications | |
| 13 | Multi-objective optimization methods | Preliminary research on the subject and investigation of current applications | |
| 14 | Bilgisayar uygulamaları-I | Preliminary research on the subject and investigation of current applications | |
| 15 | Bilgisayar uygulamaları-II | 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 | ||