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May 21 '10 at 11:28

antolikjan's gravatar image

antolikjan
226346

What are the state of the art optimization algorithms for problems with numerous local minima.

Hello,

I'm trying to fit a model that turns out to result in fitness function with loads of local minima, and simple gradient methods don't seem to come up with any good solutions (and I know from simpler models fit to the same problem that good solutions have to exist).

After doing some reading, it seems my only option are various stochastic methods such as evolutionary method or monte-carlo optimizations. My question is what are the state of the art optimization algorithms that are know to handle many local optima well. Ideally, I would like to combine the stochastic search with the gradient so that the fact that I have the 1st and 2nd order gradient of the model is exploited.

Many thanks for help, Jan

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Revision n. 2

May 21 '10 at 11:36

Joseph%20Turian's gravatar image

Joseph Turian
577551125146

What are the state of the art optimization algorithms for problems with numerous local minima.minima?

Hello,

I'm trying to fit a model that turns out to result in fitness function with loads of local minima, and simple gradient methods don't seem to come up with any good solutions (and I know from simpler models fit to the same problem that good solutions have to exist).

After doing some reading, it seems my only option are various stochastic methods such as evolutionary method or monte-carlo optimizations. My question is what are the state of the art optimization algorithms that are know to handle many local optima well. Ideally, I would like to combine the stochastic search with the gradient so that the fact that I have the 1st and 2nd order gradient of the model is exploited.

Many thanks for help, Jan

click to hide/show revision 3
Revision n. 3

May 21 '10 at 11:58

Joseph%20Turian's gravatar image

Joseph Turian
577551125146

What are the state of the art optimization algorithms for problems with numerous local minima?

I'm trying to fit a model that turns out to result in fitness function with loads of local minima, and simple gradient methods don't seem to come up with any good solutions (and I know from simpler models fit to the same problem that good solutions have to exist).

After doing some reading, it seems my only option are various stochastic methods such as evolutionary method or monte-carlo optimizations. My question is what are the state of the art optimization algorithms that are know to handle many local optima well. Ideally, I would like to combine the stochastic search with the gradient so that the fact that I have the 1st and 2nd order gradient of the model is exploited.

click to hide/show revision 4
Revision n. 4

Jul 01 '10 at 07:48

antolikjan's gravatar image

antolikjan
226346

What are the state of the art optimization algorithms for problems with numerous local minima?

I'm trying to fit a model that turns out to result in fitness function with loads of local minima, and simple gradient methods don't do not seem to come up with any good solutions (and I know from simpler models fit to the same problem that good solutions have to exist).

After doing some reading, it seems my only option are various stochastic methods such as evolutionary method or monte-carlo optimizations. My question is what are the state of the art optimization algorithms that are know to handle many local optima well. Ideally, I would like to combine the stochastic search with the gradient so that the fact that I have the 1st and 2nd order gradient of the model is exploited.

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adding state of the art tag

Jul 07 '10 at 10:18

Alexandre%20Passos's gravatar image

Alexandre Passos
2551153277421

What are the state of the art optimization algorithms for problems with numerous local minima?

I'm trying to fit a model that turns out to result in fitness function with loads of local minima, and simple gradient methods do not seem to come up with any good solutions (and I know from simpler models fit to the same problem that good solutions have to exist).

After doing some reading, it seems my only option are various stochastic methods such as evolutionary method or monte-carlo optimizations. My question is what are the state of the art optimization algorithms that are know to handle many local optima well. Ideally, I would like to combine the stochastic search with the gradient so that the fact that I have the 1st and 2nd order gradient of the model is exploited.

click to hide/show revision 6
Revision n. 6

Dec 03 '10 at 07:06

Alexandre%20Passos's gravatar image

Alexandre Passos
2551153277421

What are the state of the art optimization algorithms for problems with numerous local minima?

I'm trying to fit a model that turns out to result in fitness function with loads of local minima, and simple gradient methods do not seem to come up with any good solutions (and I know from simpler models fit to the same problem that good solutions have to exist).

After doing some reading, it seems my only option are various stochastic methods such as evolutionary method or monte-carlo optimizations. My question is what are the state of the art optimization algorithms that are know to handle many local optima well. Ideally, I would like to combine the stochastic search with the gradient so that the fact that I have the 1st and 2nd order gradient of the model is exploited.

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