Design Definition and Multidisciplinary Optimization

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Explores system architecture, concept generation methods, and the importance of managing complexity in design.

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Explores optimal transport, transforming light, inverse design optimization, and sensitivity analysis for shape optimization.

Explores energy optimization in memory systems, emphasizing the importance of memory hierarchies and trade-offs between reliability and timeliness.

Explores the design challenges and benefits of hybrid CRFs, emphasizing low loss and simultaneous optimization for improved performance.

Covers the application and optimization of a two-stage heat pump system, emphasizing accurate modeling and optimization for energy systems.

Explores examination procedures, energy system optimization, PV systems, and financial metrics.

Explores the application of deep generative models in drug discovery, focusing on designing small molecules and optimizing molecular structures.

Introduces the EPFL project based learning approach for optimizing energy systems through theory, project tasks, and tools.

Covers the Newton's local method in Python using NumPy for optimization.