Evolutionary Solver Introduction

by Tuğrul Yazar | May 22, 2012 19:59

Galapagos[1] was a great improvement when it became available natively within Grasshopper as an Evolutionary Solver. However, I couldn’t find time to examine it until recently. This examination gave me an idea of algorithmic thinking, tool making, and tool using. The first experiment shown below tries to solve equilateral triangulation, based on the Delaunay method.

Galapagos has two different solvers, named “simulated annealing solver” and “evolutionary solver” shown respectively below. Both of them are trying to reach a fitness value defined by the user. You may enter “Maximize”, “Minimize” or any numeric value to this input. It is important to formulate this value according to your design intentions. There are limited explanation links from the component inside. But it seems they are not enough. In 2022, after more than ten years, Galapagos hasn’t changed a lot. There are similar add-ons in Grasshopper, which I should also study.

I hope you may find this beginning useful if you are also trying to “solve” the evolutionary solver.

[3]

In a sense, evolutionary simulations replace design since artists can use this software to breed new forms rather than specifically design them. This is basically correct but, as I argue below, there is a part of the process in which deliberate design is still a crucial component.

De Landa, Manuel

The sad thing about artificial intelligence is that it lacks artifice and therefore intelligence.

Baudrillard, Jean

Source URL: https://www.designcoding.net/solving-the-evolutionary-solver/

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