Optimization in design problems is elusive due to the inherent multiplicity and ambiguity of the optimal for real world problems. However partial optimization of specific aspects of architecture is possible and can be implemented in both physical models [in the way hanging chains, membranes and stress induced birefringence has been used in the past] and digital simulations.
Through mainly examples and tools from the field of structural optimization, students will be introduced to ways of decomposing complex design problems into a set of input parameters and objective functions necessary for the application of optimization methods. Ways of describing geometry and constrains suitable for optimization problems will be discussed, as well as the relationship between design intentions and objective functions. Students will be required to develop a process by which they can improve measurable aspects of a design problem of their choice and produce a series of testable optimal outcomes. This process may include any combination of physical or digital models, simulations and evaluation techniques.