This page contains a selection of work from the USC Arch 517 Course: Problem Solving Using Evolutionary Systems. The course was held 1 day a week for 5 weeks in the Spring of 2011.
Galapagos, a unique feature within Grasshopper, became a tool for introducing students to the world of evolutionary problem solving. Supplemental material on genetic algorithms and evolutionary computation was also introduced for context. This included a simple VB.NET implementation of a genetic algorithm so students could understand what goes on "under the hood" in a tool such as Galapagos.
Every week, a selection of optimization problems were introduced. The students were walked through how to construct simple parametric models in Grasshopper and then use Galapagos to optimize the model based on a fitness objective.
For their final assignment, the students were asked to identify a unique optimization problem that could be used in the context of architecture.
In-Class Weekly Exercises
|Single-Objective||Exercises demonstrated the use of evolutionary computing for the purposes of single-objective optimization. Galapagos was used to optimize a parametric model using one fitness goal.||VIDEO: Single-objective exercises|
|Multi-Objective||Exercises demonstrated the use of evolutionary computing for the purposes of multi-objective optimization. Galapagos was used to optimize a parametric model using two or more fitness goals.||VIDEO: Multi-Objective exercises|
|Complex Objectives||Exercises demonstrated the use of evolutionary computing for the purposes of finding solutions to more complex design and optimization problems. The traveling salesman problem and feedback-loops with analysis software were introduced.||VIDEO: 'The Traveling Salesman' problem in an urban design context.|
Featured Student Work
Click the student's name for a more detailed look at their investigations. Pages included descriptions, images, and videos. Grasshopper files are also available for download.
|Mohamed El Sheikh|