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Show HN: A Genetic Algorithm library written in JavaScript

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Re: Show HN: A Genetic Algorithm library written in JavaScript

#31

Post by andretti1977 »

thephyber wrote: post #24
kvonhorn wrote: post #21

Earlier quoted context omitted.

Mostly links here on HN, links at /r/genetic_algorithms hitting my feed a little more often, and I'm seeing GAs referenced with designing neural nets in random articles. I'm guessing that it's the last one that would drive renewed interest if that is indeed what I've been seeing, though I'm wondering if there is interest in applications for GAs outside of AI/ML.

I believe AutoCAD implemented a service which uses a GA to design an optimal solution for desired engineering specs. At their core, GAs are search algorithms so they are relevant in lots of fields. Combine them with digital simulations (eg. physics, games, war) and you can search at far faster than life speeds.

GA are used for electronic circuit connection design (sorry, i don't the correct english name for the line printed on the circuits that connects different pins). GA are used to solve the problem of laying out them avoiding intersection. GA are used to design antennas. They are often used in travelling salesman like problems. GA and GP would be vey useful also in some other context like finding sequences of actions if only they could benefit from GPU like neural net did, but gpu aren't suitable for GA/GP and it's a pity since in GA/GP you can understand the inner structure easier than in a neural net where simply you don't know why the net took that decision.

Re: Show HN: A Genetic Algorithm library written in JavaScript

#32

Post by throwaway316943 »

andretti1977 wrote: post #31
thephyber wrote: post #24

Earlier quoted context omitted.

I believe AutoCAD implemented a service which uses a GA to design an optimal solution for desired engineering specs. At their core, GAs are search algorithms so they are relevant in lots of fields. Combine them with digital simulations (eg. physics, games, war) and you can search at far faster than life speeds.

GA are used for electronic circuit connection design (sorry, i don't the correct english name for the line printed on the circuits that connects different pins). GA are used to solve the problem of laying out them avoiding intersection. GA are used to design antennas. They are often used in travelling salesman like problems. GA and GP would be vey useful also in some other context like finding sequences of actions if…

I’m sure you could find a way to do GAs on a GPU. If you could have generations measured in billions of individuals and compute all of their fitness, mutation, crossover in parallel it should drastically speed up the algorithm.

Re: Show HN: A Genetic Algorithm library written in JavaScript

#33

Post by solaxun »

djaque wrote: post #28
kvonhorn wrote: post #25

Earlier quoted context omitted.

What field are you in?

Particle accelerator physics. They are used in the optimization of charged particle optics.

Purely out of curiosity - is there something about them that makes them better than other optimization algorithms, e.g. simulated annealing, random local search etc, or for continuous functions gradient descent and the like. Seems like GA's are always glossed over as a relic of past times, it's pretty interesting to hear about them in practice somewhere!

Re: Show HN: A Genetic Algorithm library written in JavaScript

#34

Post by panda88888 »

andretti1977 wrote: post #31
thephyber wrote: post #24

Earlier quoted context omitted.

I believe AutoCAD implemented a service which uses a GA to design an optimal solution for desired engineering specs. At their core, GAs are search algorithms so they are relevant in lots of fields. Combine them with digital simulations (eg. physics, games, war) and you can search at far faster than life speeds.

GA are used for electronic circuit connection design (sorry, i don't the correct english name for the line printed on the circuits that connects different pins). GA are used to solve the problem of laying out them avoiding intersection. GA are used to design antennas. They are often used in travelling salesman like problems. GA and GP would be vey useful also in some other context like finding sequences of actions if…

Circuit route design :)

Re: Show HN: A Genetic Algorithm library written in JavaScript

#35

Post by smeernof »

solaxun wrote: post #33
djaque wrote: post #28

Earlier quoted context omitted.

Particle accelerator physics. They are used in the optimization of charged particle optics.

Purely out of curiosity - is there something about them that makes them better than other optimization algorithms, e.g. simulated annealing, random local search etc, or for continuous functions gradient descent and the like. Seems like GA's are always glossed over as a relic of past times, it's pretty interesting to hear about them in practice somewhere!

Haven't worked on them a lot recently, but AFAIK, the population based nature helps them escape local minima and do a better job at exploring the solution space.

Re: Show HN: A Genetic Algorithm library written in JavaScript

#36

Post by djaque »

solaxun wrote: post #33
djaque wrote: post #28

Earlier quoted context omitted.

Particle accelerator physics. They are used in the optimization of charged particle optics.

Purely out of curiosity - is there something about them that makes them better than other optimization algorithms, e.g. simulated annealing, random local search etc, or for continuous functions gradient descent and the like. Seems like GA's are always glossed over as a relic of past times, it's pretty interesting to hear about them in practice somewhere!

We use them because they are particularly well suited for multi-objective optimization. They are also a global techniqe as opposed to gradient based methods and have great scaling properties. Important because each evaluation of the objective function takes ten minutes for us.

GAs have found a niche in a lot of "obscure" engineering situations. Anything where you need to optimize an expensive black box function is at least worth a try with a GA. I know they are used in analog IC design, civil engineer, and aerospace.

Re: Show HN: A Genetic Algorithm library written in JavaScript

#37

Post by matsemann »

solaxun wrote: post #33
djaque wrote: post #28

Earlier quoted context omitted.

Particle accelerator physics. They are used in the optimization of charged particle optics.

Purely out of curiosity - is there something about them that makes them better than other optimization algorithms, e.g. simulated annealing, random local search etc, or for continuous functions gradient descent and the like. Seems like GA's are always glossed over as a relic of past times, it's pretty interesting to hear about them in practice somewhere!

They can be very good when there are multiple objectives / tradeoffs. I wrote my thesis on that, which includes an introduction to the concept and how it works if you're interested. http://master.matsemann.com/

Re: Show HN: A Genetic Algorithm library written in JavaScript

#38

Post by matsemann »

tlarkworthy wrote: post #8

Nueral network tech went through a weird period and then back to basics (back prop) just with massive computation (and simple activation functions) with fabulous results. I wonder if similar things could be done with other old school techniques like GA. Does anyone know if we have tried massive ones?

For GAs the expensive part is often the fitness function. So it's very problem dependant.

Re: Show HN: A Genetic Algorithm library written in JavaScript

#39

Post by phyzix5761 »

bmh100 wrote: post #26
nyxyn wrote: post #19

Earlier quoted context omitted.

Thanks for your comment. This algorithm keeps the best candidates through every generation.

I see that, but the best candidate of the current generation is not necessarily the best candidate ever seen. Reproduction and mutation can lead to the best solution of a given generation being worse than the generation before it.

The best candidate is always kept throughout the whole evolution process. If you find the best candidate in the second generation, for example, it will be kept all the way to the end.

Re: Show HN: A Genetic Algorithm library written in JavaScript

#40

Post by andretti1977 »

throwaway316943 wrote: post #32
andretti1977 wrote: post #31

Earlier quoted context omitted.

GA are used for electronic circuit connection design (sorry, i don't the correct english name for the line printed on the circuits that connects different pins). GA are used to solve the problem of laying out them avoiding intersection. GA are used to design antennas. They are often used in travelling salesman like problems. GA and GP would be vey useful also in some other context like finding sequences of actions if…

I’m sure you could find a way to do GAs on a GPU. If you could have generations measured in billions of individuals and compute all of their fitness, mutation, crossover in parallel it should drastically speed up the algorithm.

That's exactly the point: is it possible? From my understandings, GPU allows massive parallel matricial calculations but that's not the case for mutations and crossovers (which involves random selection of mutate gene). Even so complex fitness functions (that are based on mathematical operation that takes into account more data per point like a moving average) couldn't be converted to matricial calculus.
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