This course gives an overview of the packing problem and its applications in design and space planning. Viewers will learn how to represent the goals of a packing problem through computing the overlaps between regions in a model. The session also covers a variety of approaches for optimizing models with multiple objectives, including optimizing for all objectives at once, optimizing for a single objective while setting the rest as constraints, and optimizing for a single objective represented as a function of the other objectives.
The second part of the course goes deeper into the packing problem and its application in design and architecture. We will first extend the basic packing model from the previous week to model a basic site planning problem in architecture. We will then extend the model by adding a local optimization routine to the model which ensures better quality results with each design. This will demonstrate the potential of hybrid optimization techniques that use top-down metaheuristic algorithms to optimize models which themselves contain local optimization routines to ensure that the best solutions are found in the shortest amount of time.
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