MECH 888: Nonlinear Optimization in Engineering
Topics covered:
• Algorithms for constrained and unconstrained nonlinear optimization;
• Gradient-based and gradient-free methods (e.g. genetic algorithms).
• Stochastic Gradient in Deep Neural Networks/Machine Learning.
Applications drawn from:
• Shape and topology optimization of structures
• Material optimization
• Machine learning
• And more!
Select a term project from your own field of interest, (e.g. shape and topology optimization, materials optimization, financial portfolio optimization, optimization of chemical reactions, optimization of electromagnetic devices, image and pattern recognition, traffic optimization, optimal design in nature, machine learning algorithms, etc.
For more information contact:
Prof. Florin Bobaru
fbobaru2@unl.edu
(402) 472-8348