Engineering Optimization

Course	T-423-ENOP
Semester	20241
ETCS	6
Core	No

Year	1. year
Semester	Spring 2024
Level of course	First cycle - Advanced / Second cycle - Introductory
Type of course	Elective
Prerequisites	T-101-STA1, Calculus I T-211-LINA, Linear Algebra
Schedule	Taught every day for three weeks.
Lecturer	Slawomir Marcin Koziel
Content
Level of course:           3. Undergraduate, advanced / 4. Graduate, introductory. Type of course:            Elective. Prerequisites:  1)Working knowledge of Matlab programming; 2) Calculus (elementary linear algebra, in particular, vector/matrix operations and linear systems; Basic knowledge of derivatives, including Taylor expansion).The course introduces the concept and methods of engineering optimization. Major topics discussed throughout the course are: formulation of unconstrained and constrained optimization problems, objective functions, classification of optimization methods, first- and second-order optimality conditions, gradient-based search methods, derivative-free optimization, stochastic search methods including multi-agent systems and evolutionary algorithms, multi-objective optimization, surrogate-based optimization with focus on space mapping, functional and physical surrogate modeling, design of experiments, model selection and validation, as well as solving real-world engineering optimization problems with interfacing of commercial simulators. The relevant material concerning Matlab programming as well as calculus in the scope necessary for the course will also be given.Reading material:               Lecture slides provided by the teacher
Learning outcome - Objectives
Upon completing the course, the students should be able to:(1) Formulate engineering optimization problem, corresponding objective functions and constraints,(2) Select appropriate optimization/modeling methodology,(3) Implement basic optimization and modeling procedures as well as develop necessary Matlab code,(4) Solve problems using existing packages, in particular Matlab and Matlab’s Optimization Toolbox,(5) Visualize the optimization process and the results.
Course assessment
Grades are based exclusively on the assessment of the solutions to the practical exercises. Requirement regarding the solution format and other details will be given during the first lecture.
Reading material
No reading material found.
Teaching and learning activities
Language of instruction	English