Design Definition and Multidisciplinary Optimization

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Related lectures (31)

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Design Optimization: Principles and Applications

Covers design optimization principles, virtual prototypes, multi-objective optimization, and challenges in the field.

Chemical Reaction Optimization: Multi-Task Learning

Explores multi-task learning for accelerated chemical reaction optimization, showcasing challenges, automated workflows, and optimization algorithms.

MILP Model and Typical Days by FM

Discusses MILP model, typical days, clustering, and extreme periods analysis in energy systems optimization.

Geometric Computing Laboratory: Inverse Design Optimization

Explores inverse design optimization in geometric computing, covering topics such as deployable structures, material-aware design, and programmed materials.

Optimisation Strategies: Energy Systems Modelling and Optimization

Explores solving strategies for energy system optimization problems and different types of optimization approaches.

Optimization: Classical Problems

Covers classical optimization problems, brute force algorithms, and integer linear optimization.

Structures in Non-Convex Optimization

Covers non-convex optimization, deep learning training problems, stochastic gradient descent, adaptive methods, and neural network architectures.

Fluorescent Protein Stability Assessment

Covers protein stability assessment using RFP and GFP, flow cytometry, mutagenesis, calcium reporters, and CRISPR-Cas9 experiments.

Energy System Optimization at EPFL

Explores the optimization of EPFL's energy system through defining demands, analyzing options, and applying optimization techniques.

Design Optimization in ChemBio

Explores the design optimization of sensors and bioluminescent proteins for drug monitoring and metabolite visualization.