Later we shall discuss how GAs can be used to solve a constrained optimization problem. Let us consider the following maximization problem: Abbildung in dieser Leseprobe nicht enthalten Although a maximization problem is considered here, a minimization problem can also be handled using Gas. The working of Gas is completed by performing the following tasks:
Feb 27, 11 6: Musical Transference I've seen a few of those done as thesis. The most boring, humorless, insert word for opposite of playful heretopic you can pick.
Together, not so much I haven't heard that term used outside of IT.
You are going for some highly abstract concepts here. I need you to think about your future employability. Spending a few years on something you'll probably never implement is kind of sad. Have you though of covering something more practical?
Waterproofing comes to mind. Feb 27, 11 7: I would specifically focus on the "greedy" type of algorithms, and what they mean - what makes them distinct from parametric design in general.
Feb 28, 11 1: George's Fields You should make your thesis about waterproofing a building using only recycled, re-purposed douche bags or bottles. For the musical transference thing: It reads as another bullshit about everything but in the end about nothing.
But seeing as I am sort of a self-taught musician I sometimes find myself working on some projects in the same way that I worked on some music if this is vague i am sorry, it is to me too as in i don't have an exact explanation.
Architecture has rules but i'm not talking about code or structure you can't build this etc. Anyone else has this problem? The thing with greedy algorithms is that they extract optimal substructures from a pool of solutions so the solutions are already generated.
Now the thing is that greedy works when you can't compute all the variants because it will take too long so you're only interested in a good-enough solution but sometimes greedy gives you the worst one Parametric design, as in Grasshopper not Revit, seems to be more about the geometry than about the actual project.
What i am saying is why don't you use parametrics and comp-science for "standard", immediate architecture say social housing.
Say you have S - square meters of site. You want S' of program. Solve this problem within the constraints: But you can do it. You can generate say 10 20 project iterations and compare them and so on I think that's more interesting and useful that blobs and spikes and minimal surfaces and the lot.
Again I'm not pitching a topic to my dissertation supervisor. I'm just trying to come up with something that is relevant, meaningful and interesting for me to get into. I'm not aiming for originality or that kind of shit, and i know waterproofing is essential but come on I'm only interested in the 3rd topic but they want 3 examples so i'll have to keep digging.
Feb 28, 11 2: It sounds sort of similar to 'hedonic model', which is a model that says that you break a thing down into its component parts and figure out what the effect of each one is. Searching for this term might be helpful in finding systems that use this method, if not buildings.
They're sometimes used in real estate models I think; I ran across the term in a statistics textbook on geographically weighted regression, so it's not like I've done any kind of literature review! I don't have the publication right here did a presentation on integrating GIS analysis with performance metrics in a way that I think might be similar to what you're getting at in a project somewhere.
As I recall, he or she was looking for empty parcels and using geographic analysis and parametric modeling to create buildings on the sites that were responsive to their environments.
I don't know if that's interesting to you, but it sure is to me! Feb 28, 11 3: That's who it was.
The project I'm referring to is this: It's still an interesting example of how you can use data to create things.The topic of this thesis is the question of how exactly GA and NN can be combined, i.e.
especially how the neural network should be represented to get good results from the genetic algorithm. Overview Chapter 1 introduces the basic concepts of this thesis: neural networks and genetic algo-rithms.
Master Thesis Report, IDE School of Information Science, Computer and Electrical Engineering Halmstad University. II Three bio-inspired algorithms: genetic algorithm (GA), ant colony optimization (ACO), and imperialist competitive algorithm (ICA) is suggested.
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Williams, Kevin Richard, "Applications of Genetic Algorithms to a Variety of Problems in Physics and Astronomy. " Master's Thesis, University of Tennessee, ADAPTIVE, MULTI-OBJECTIVE JOB SHOP SCHEDULING USING GENETIC ALGORITHMS Haritha Metta ADAPTIVE, MULTI-OBJECTIVE JOB SHOP SCHEDULING USING GENETIC ALGORITHMS Unpublished thesis submitted for the Master’s degree and deposited in the University of.
parameter selection for genetic algorithm (ga)-based simulation optimization a thesis submitted to the department of industrial engineering and the institute of engineering and sciences.