Explore the fundamentals of engineering design optimization in this 1 hour 20 minute lecture from Stanford University's AA222 / CS361 course. Delve into linear constrained optimization techniques as Joshua Ott guides you through the mathematical and algorithmic foundations essential for tackling complex engineering problems. Gain insights into derivative and derivative-free approaches for both linear and non-linear problems, with a focus on multidisciplinary design optimization. Discover quantitative methodologies for addressing various challenges in the field, including multi-objective optimization, automatic differentiation, uncertainty handling, experimental design point selection, and optimization strategies for expensive evaluations. Learn how these concepts apply to real-world scenarios, from aircraft design to automated vehicle development. Access additional course materials and enrollment information through the provided links to enhance your understanding of this crucial aspect of engineering design.
Overview
Syllabus
Stanford AA222 / CS361 Engineering Design Optimization I Linear Constrained Optimization
Taught by
Stanford Online