Multidisciplinär optimering (Multidisciplinary Optimization) 7,5 hp

Undervisningen bedrivs på engelska.

Kursinnehåll

The course enables engineering students to apply optimization techniques in the engineering process to optimize product realization aspects. The applications can be broad and multidisciplinary. This is achieved by utilizing both classical optimization algorithms and software for modelling objective functions by using one software as input to another.


The course includes the following elements:

• Introduction to optimization driven design using parameter optimization and structural optimization
• Univariate optimization, direct methods, local descent, line search
• The steepest descent method, Newton’s method, Karush-Kuhn-Tucker conditions (KKT),
• Direct methods: Nelder-Mead Simplex method
• Heuristic methods: Population methods (genetic algorithms, differential evolution), simulated annealing
• Multi-objective non-linear optimization and their industrial applications: Pareto optimality, dominance, NSGA2
• Surrogate modeling using neural networks
• Implementation of optimization algorithms using Julia programming

Förkunskapskrav

Passed courses of at least 150 credits in the program Industrial Product Realisation, or a bachelor’s degree (i.e the equivalent of 180 ECTS credits at an accredited university) with at least 90 credits in Mechanical Engineering, Product Development, Materials Engineering, Manufacturing Engineering, Industrial Engineering, Civil or Construction Engineering, or the equivalent. The bachelor’s degree should comprise a minimum of 15 credits in Mathematics. Proof of English proficiency is required.

Utbildningsnivå: Avancerad nivå A1N
Kurskod/Ladokkod: TMOR25
Kursen ges vid: Tekniska Högskolan Last modified 2024-11-11 14:55:08