To obtain basic concepts of optimization methods with applications to electronics engineering. Using a combination of lectures and project based activities, students will develop an understanding of the overall design optimisation process and the performance of different optimisation algorithms, when applied to solve real engineering cases.
Stanislaw H. Zak, Edwin K.P.Chong, Introduction to Optimization, Wiley, 2013
Muhammad Fahri, Hassan Bevrani, Optimization in Electrical Engineering, Springer, 2019, 978-3030053086
Other Sources
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Course Schedules
Week
Contents
Learning Methods
1. Week
Introduction to optimization
Presentation and practice
2. Week
Mathematical review (matrix theory)
Presentation and practice
3. Week
Mathematical review (linear equations)
Presentation and practice
4. Week
Linear transformations, geometric view of the transformations
Presentation and practice
5. Week
Unconstraint optimization, one dimensional search methods
Presentation and practice
6. Week
Constraint optimization
Presentation and practice
7. Week
Problems with Inequality Constraints
Presentation and practice
8. Week
Midterm
9. Week
Gradient methods
Presentation and practice
10. Week
Newton’s method
Presentation and practice
11. Week
Solving linear equations
Presentation and practice
12. Week
Linear Programming
Presentation and practice
13. Week
Simplex method
Presentation and practice
14. Week
Integer linear Programming
Presentation and practice
15. Week
16. Week
17. Week
Assessments
Evaluation tools
Quantity
Weight(%)
Midterm(s)
1
25
Quizzes
1
25
Final Exam
1
50
Program Outcomes
PO-1
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied information in these areas to model and solve engineering problems.
PO-2
Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
PO-3
Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way so as to meet the desired result; ability to apply modern design methods for this purpose. (Realistic constraints and conditions may include factors such as economic and environmental issues, sustainability, manufacturability, ethics, health, safety issues, and social and political issues according to the nature of the design.)
PO-4
Ability to devise, select, and use modern techniques and tools needed for engineering practice; ability to employ information technologies effectively.
PO-5
Ability to design and conduct experiments, gather data, analyze and interpret results for investigating engineering problems.
PO-6
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
PO-7
Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language.
PO-8
Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.
PO-9
Awareness of professional and ethical responsibility.
PO-10
Information about business life practices such as project management, risk management, and change management; awareness of entrepreneurship, innovation, and sustainable development.
PO-11
Knowledge about contemporary issues and the global and societal effects of engineering practices on health, environment, and safety; awareness of the legal consequences of engineering solutions.
Learning Outcomes
LO-1
Explain the objective function, decision variables and constraint functions in the optimization model
LO-2
Understand basic theoretical principles in unconstraint and constraint optimisation
LO-3
Know different optimisation algorithms and their capabilities
LO-4
Solve engineering optimisation problems through the use of the available optimisation software
