Nevşehir Hacı Bektaş Veli University Course Catalogue
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| Year/Semester of Study | 1 / Fall Semester | ||||
| Level of Course | 2nd Cycle Degree Programme | ||||
| Type of Course | Optional | ||||
| Department | ELECTRICAL AND ELECTRONICS ENGINEERING (MASTER) | ||||
| Pre-requisities and Co-requisites | None | ||||
| Mode of Delivery | Face to Face | ||||
| Teaching Period | 14 Weeks | ||||
| Name of Lecturer | SUAD BAŞBUĞ (suad@nevsehir.edu.tr) | ||||
| Name of Lecturer(s) | |||||
| Language of Instruction | Turkish | ||||
| Work Placement(s) | None | ||||
| Objectives of the Course | |||||
| To teach classical and modern optimization techniques; to gain the ability to apply them to engineering problems; to gain an understanding of the importance, scope, and present state of optimization theory. | |||||
| Learning Outcomes | PO | MME | |
| The students who succeeded in this course: | |||
| LO-1 | Being aware of engineering importance of optimization as a mathematical tool |
PO-1 Sufficient knowledge in mathematics, science and engineering related to their branches; the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems. PO-2 The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose. PO-3 The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.) |
Examination |
| LO-2 | Ability to apply classical optimization techniques to real engineering problems |
PO-2 The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose. PO-3 The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.) PO-11 Information on the effects of engineering applications on health, environment and safety in the universal and social dimensions and the problems of the times; awareness of the legal consequences of engineering solutions. |
Examination |
| LO-3 | To have basic knowledge about modern optimization methods |
PO-1 Sufficient knowledge in mathematics, science and engineering related to their branches; the ability to apply theoretical and practical knowledge in these areas to model and solve engineering problems. PO-2 The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modeling methods for this purpose. PO-3 The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. (Realistic constraints and conditions include such issues as economy, environmental issues, sustainability, manufacturability, ethics, health, safety, social and political issues, according to the nature of design.) PO-5 Ability to design experiments, conduct experiments, collect data, analyze and interpret results for examination of engineering problems. |
Examination |
| PO: Programme Outcomes MME:Method of measurement & Evaluation |
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| Course Contents | ||
| Introduction to Optimization Theory Single Variable Optimization, Multivariable Unconstrained Optimization. Multivariable Constrained Optimization Linear Programming Simplex Algorithm Nonlinear Programming Search Methods, Range Reduction Methods Multivariable Unconstrained Search Methods Dynamic Programming Modern Methods Properties of Stochastic Methods Introducing Metaheuristic Algorithms Differential Development Algorithm 1 Differential Development Algorithm 2 | ||
| Weekly Course Content | ||
| Week | Subject | Learning Activities and Teaching Methods |
| 1 | Introduction to Optimization Theory | Lecture, question and answer, discussion |
| 2 | Single Variable Optimization, Multivariable Unconstrained Optimization. | Lecture, question and answer, discussion |
| 3 | Multivariate Constrained Optimization | Lecture, question and answer, discussion |
| 4 | Linear Programming | Lecture, question and answer, discussion |
| 5 | Algorithm | Lecture, question and answer, discussion |
| 6 | Nonlinear Programming | Lecture, question and answer, discussion |
| 7 | Search Methods, Range Reduction Methods | Lecture, question and answer, discussion |
| 8 | mid-term exam | |
| 9 | Multivariable Unconstrained Search Methods | Lecture, question and answer, discussion |
| 10 | Dynamic Programming | Lecture, question and answer, discussion |
| 11 | Modern Methods | Lecture, question and answer, discussion |
| 12 | Properties of Stochastic Methods | Lecture, question and answer, discussion |
| 13 | Introduction to Algorithms Metaheuristic | Lecture, question and answer, discussion |
| 14 | Differential Development Algorithm 1 | Lecture, question and answer, discussion |
| 15 | Differential Development Algorithm 2 | Lecture, question and answer, discussion |
| 16 | final exam | |
| Recommend Course Book / Supplementary Book/Reading | ||
| 1 | W. Forst and D. Hoffmann, Optimization—Theory and Practice. Springer Science & Business Media, 2010. | |
| 2 | S. S. Rao, Engineering Optimization: Theory and Practice, 4 edition. Hoboken, N.J: Wiley, 2009. | |
| Required Course instruments and materials | ||
| Course book, laptop computer, projector | ||
| Assessment Methods | |||
| Type of Assessment | Week | Hours | Weight(%) |
| mid-term exam | 8 | 1 | 40 |
| Other assessment methods | |||
| 1.Oral Examination | |||
| 2.Quiz | |||
| 3.Laboratory exam | |||
| 4.Presentation | |||
| 5.Report | |||
| 6.Workshop | |||
| 7.Performance Project | |||
| 8.Term Paper | |||
| 9.Project | |||
| final exam | 16 | 1 | 60 |
| Student Work Load | |||
| Type of Work | Weekly Hours | Number of Weeks | Work Load |
| Weekly Course Hours (Theoretical+Practice) | 3 | 14 | 42 |
| Outside Class | |||
| a) Reading | 3 | 11 | 33 |
| b) Search in internet/Library | 3 | 11 | 33 |
| c) Performance Project | 3 | 10 | 30 |
| d) Prepare a workshop/Presentation/Report | 0 | ||
| e) Term paper/Project | 3 | 10 | 30 |
| Oral Examination | 0 | ||
| Quiz | 0 | ||
| Laboratory exam | 0 | ||
| Own study for mid-term exam | 5 | 1 | 5 |
| mid-term exam | 1 | 1 | 1 |
| Own study for final exam | 5 | 1 | 5 |
| final exam | 1 | 1 | 1 |
| 0 | |||
| 0 | |||
| Total work load; | 180 | ||