goat

goat is an optimization solver add-on component. It perfectly complements galapagos, David Rutten's evolutionary solver based on a randomized core. goat pursues a mathematical rigorous approach and relies on gradient-free optimization algorithms, delivering fast and deterministic results. At every run, goat will yield the same optimal result.

goat is a drop-in replacement for galapagos. It is based on David Rutten's galapagos GUI and interfaces NLopt, a collection of mathematical optimization libraries.

Tutorials

For getting started with optimization in parametric modelling environments in general and with goat in special, check out our presentation slides onĀ Geometry and Optimization with several comprehensive examples.

Once you are familiar with the basics of optimization, head over to our comprehensiveĀ documentation on goat's different configuration options.

Inequality Constraints???

Hi,

Firstly, thanks for the great tool! I really appreciate the greatest descent approach which is great for situations where computation times are long and genetic algorithms are not feasible!

My question is: Is there any way to incorporate inequality constraints into Goat?

This would be of great benefit to structural problems where for example we want to minimise steel weights but ensure that stresses and deflection limits are not exceeded.

Thanks,

Sam

  • up

    Simon Flöry

    Hi Sam,

    You may incorporate inequality constraints via "Barrier Functions" into goat. A detailed explanation is beyond the scope of this forum, instead I provide a link to wikipedia: https://en.wikipedia.org/wiki/Barrier_function

    If you need further support on this, please send us an email (goat@rechenraum.com) and we'll see how we can help you further.

    best, simon