Alternatives to Genetic Algorithms in Architectural Design

Hello everyone,

I'm not sure if this is the right forum for it but it's the most relevant I know !

I'm working on my master thesis thesis right now, I started looking into parametric design issues and eventually found out about genetic algorithms on which I found extensive researches, projects,... !
I looked into it and ended up on a few papers which I believe are the jumpstart for my master thesis.

"Galapagos; on the logic and limitations of generic solvers" by David Rutten
Article in Architectural Design 83(2) March 2013
"Black-box optimisation methods for architectural design" by Thomas Wortmann and Giacomo Nannicini
Conference Paper: CAADRIA 2016, At Melbourne, AU, Volume: 177-186

So I started looking into alternatives to genetic algorithms in architectural design.

So far, I've ended up on :

Thomas Wortmann's work with the surrogate(or model) based optimization approach!
You can check out the tool he developped for GH (Opossum):
http://www.food4rhino.com/app/opossum-optimization-solver-surrogate...
Judyta Cichocka's work, specially with the Swarm approach
You can check out the tool she developped for GH (Silvereye):
http://www.food4rhino.com/app/silvereye-pso-based-solver

And that's it !!! I've been researching through article references (mainly on "researchgate") but I'm now stuck in a loop of references I already visited!
That probably means the litterature on the subject is not (yet) extended but I might probably be missing something.
The keywords make it difficult to search : "optimisation", "algorithms", "architecture", send me most of the time to computational engineering and deep mathematics papers I unfortunately do not have the background knowledge to comprehend !

So there it is !
If you have any clue of where (or how ! ) I should be looking, please tell me :)
I know Mr Rutten is pretty active on the forum so hopefully... (fingers crossed :p) !
Also if you have any good tips for getting into algorithms in general (you think could help), I'd be glad to hear(read) it ! A book, tutorials maybe ?!

So, autors, architects, projects books, articles, conferences I should go to,
specialized architecture offices/studios (I'm also looking for an internship so ...).

If you know about a more appropriate forum please let me know !

If you want to get deeper into this, you can contact me at :

e1635331@student.tuwien.ac.at
tdissaux@student.ulg.ac.be

My master thesis is due for may 2018 but I have a paper to write for January 2018 in order to be elligible for a PHD program afterwards.
What I mean by that is that if you read this message in 6 month, I'll still be open to discussion !

I am right now an erasmus student at TUWien (Vienna) but my main university is The university of Liège in Belgium.
I can handle French, English, Italian litterature and eventually Dutch if really you think it's worth it ! I have access to most online libraries via my university's portals so access shouldn't be an issue !

I'm very excited to hear from you

I wish you all a great day,

Cheers,

Thomas

Replies to This Discussion

Permalink Reply by David Rutten on April 30, 2017 at 4:10am

When it comes to solver algorithms, there's two broad categories: specific and generic. Specific solvers know in advance what sort of problem they will be called upon to deal with and as such tend to be fast and accurate. They will however have to be written for every new problem which is not exactly the same as an old problem. Hence, as an end-user you may have to write one yourself. Generic solvers on the other hand can tackle a wide variety of problems and the end-user merely has to set up the goals and constraints. However, this flexibility comes at a price, usually speed.

There's literally thousands upon thousands of academic papers about specific algorithms out there, covering anything from networking to databases to geometry to natural language to visualisation to whatever. The list of generic solvers however is much smaller. The most famous ones being Divide-and-Conquer (fast for low dimensional cases, doesn't scale well to high dimensionality), Uphill Search (good for quickly finding local maxima, strong dependence on starting point), Evolutionary **** (works well in high dimensions, slow but flexible), Annealing (works well in high dimensions, good for exploring the entire problem space, good for finding quick approximate solutions), Machine Learning (very big category, lots of strengths and weaknesses).

You may also want to look into physical simulators, which can be very effective solvers if the problem can be formulated in terms of forces acting on vertices. Kangaroo specifically was designed with architecture in mind.

If you want to know about algorithms specific to geometry, a good read is; 'Discrete and Computational Geometry' by Satyan L. Devadoss and Joseph O'Rourke, Princeton University Press (2011), ISBN 978-0-691-14553-2

A detailed (and in my opinion not very readable) account of evolutionary algorithms can be found in; 'Evolutionary Algorithms in Theory and Practice' by Thomas Bäck, Oxford University Press (1996), ISBN 0-19-509971-0

Decent introduction to algorithmics; 'Algorithm Design' by Jon Kleinberg and Éva Tardos, Pearson Education (2006), ISBN 0-321-37291-3

and; 'Introduction to Algorithms (second edition)' by Thomas Cormen, Charles Leiserson, Ronald Rivest and Clifford Stein, MIT Press (2001), ISBN 0-262-03293-7

Permalink Reply by Mateusz Zwierzycki on April 30, 2017 at 4:17am

You might also take a look at David's blog, and another one of his papers (you can find this link on the blog).

Generally in arch academia (the GH-oriented part) there isn't much more than Goat, Octopus, SilverEye and Galapagos... and all of those optimization solvers - if treated as a black box - work the same. You have some parameters, you want to set them in a way that yields the highest fitness (or many fitness values like with Octopus), the solver tries to find the right values for the parameters.

The choice of the solver is what is important in the end, as they work best for different kinds of optimization problems. Like with any heuristic method, you always have to care about the price of the meal.

Permalink Reply by Thomas Dissaux on April 30, 2017 at 5:01am

First, Thank you so much,
I wasn't expecting such quick feedback !

David's blog is already in my favourites tab but I didn't know about that paper ! Thank You!

So I will definitely have a look at the litterature (my amazon tab is open as I'm writing this :p),
In the mean time I feel I should add some precisions. I would like to focus on architectural practice specifically and questions adressed in surveys such as these :

The second paper showing a real interest from enthousiast architects towards INTERACTIVE and FAST optimization tools with "deep" control without going into complexe programming.
As I said I realize there are tons of papers on optimization, but usually they concern engineering, and I'm not qualified to either understand or to transpose those theories to the architectural design process.
That being said I have to dive into more specific literature but even then it feels a bit to ambitious for a master thesis. (We'll see ! Also I wish for a PHD so ... )

I'm glad to see the interest, hopefully the discussion keeps going :)

Cheers

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