Overview:
A project that uses genetic algorithms to optimize material selection for building envelopes, balancing thermal resistance and cost.
This code is a variation of a genetic algorithm I developed while working at BCK Architecture. The original algorithm optimizes material selection for sound absorption, based on user-defined T20 goals, material groupings, and sound raytracing data. It evaluates material impact points and prioritizes the most absorbent areas to enhance acoustic performance. It was also combined with Rhino 3D extracting the data of the surfaces directly from the model and once the optimization was performed, return the new surfaces with the new materiasl names.
Key Features:
Genetic Algorithm: Determines optimal material combinations.
Material Library: Customizable JSON file with resistance and cost data.
Fitness Function: Balances resistance and cost, penalizing excess spending.