Course Description:

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Within the conceptual phase of design, designers uncover different aspects of a design problem, synthesize requirements and objectives into design alternatives, evaluate the generated solutions, and find suitable solutions through an iterative process.  In the recent decade, computational early-stage design tools along with multi-objective search algorithms have been developed to generate abundant design alternatives, provide a real-time numeric assessment of solutions' performance, and assist designers in making appropriate design decisions. In addition, evolutionary design exploration methods, mainly using a genetic algorithm, have been increasingly employed to allow the exploration of a population of solutions, to prevent designers from fixation on initial concepts, and to expand the diversity of design alternatives to a manageable extent.

This course aims to introduce computational design exploration methodologies that help designers to explore diverse possible design solutions to a multi-objective design problem, make informed decisions, resolve conflicting design goals, and consider quantitative and qualitative design objectives simultaneously.

Students are expected to have basic parametric design skills, but appropriate learning materials will be provided for students who need further studies and practice in CAD and parametric modeling.

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