[SciPy-Dev] scipy.optimize.anneal - deprecation
Robert Lucente - Pipeline
rlucente at pipeline.com
Tue Oct 14 07:20:02 EDT 2014
"Maybe the ?smooth" restriction in the basin hopping documentation should be
removed"
Instead, could we add words like if smooth ... . if non-smooth ...
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1. scipy.optimize.anneal - deprecation (Robert Lucente - Pipeline)
2. Re: scipy.optimize.anneal - deprecation (Jacob Stevenson)
----------------------------------------------------------------------
Message: 1
Date: Mon, 13 Oct 2014 23:45:33 -0400
From: "Robert Lucente - Pipeline" <rlucente at pipeline.com>
Subject: [SciPy-Dev] scipy.optimize.anneal - deprecation
To: <scipy-dev at scipy.org>
Cc: Robert Gmail Backup 1 Lucente Gmail Backup 1
<robert.backup.lucente at gmail.com>
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Hummm. I think I am missing something fundamental.
The official doco for scipy.optimize.basinhopping
(http://docs.scipy.org/doc/scipy-0.13.0/reference/generated/scipy.optimize.b
asinhopping.html) states "Basin-hopping is a stochastic algorithm which
attempts to find the global minimum of a smooth scalar function". The key
word to note is smooth. The non-math version of smooth is that there are no
gaps and no breaks. Also, there are no kinks and no corners. For a more in
depth explanation of this refer to pages 297 - 298 of Optimization Modeling
with Spreadsheets, Second Edition by Kenneth R. Baker. The math version is
that the functions are continuous and at least twice continuous
differentiable. Please note that the second derivative must also be
continuous. For a more in depth explanation of this refer to pages 11 - 12
of Introduction to Optimum Design, Third Edition by Jasbir Arora.
What happens when the problem you are dealing w/ is not smooth? You can't
use basin hopping. For example, a price schedule with a price break is a
standard example of a non-smooth function. My personal and immediate
non-smooth problem is placing advertising in available time slots.
Also, the SciPy lecture notes
(http://scipy-lectures.github.io/advanced/mathematical_optimization/#smooth-
and-non-smooth-problems) states "2.7.1.2. Smooth and non-smooth problems ...
Optimizing smooth functions is easier"
Simulated annealing is not perfect. It does have issues like having a lot of
knobs to turn.
Bechmarks are a tough thing. My only comment is that smooth and non-smooth
should be 2 different sets of benchmarks. BTW, I love the comment "I got fed
up with the current attitude of most mathematicians/numerical optimization
experts, who tend to demonstrate the advantages of an algorithm based on
"elapsed time" or "CPU time" or similar meaningless performance indicators"
Minor nit: I think that there is a disconnect between the code for SA and
its doco. The doco says "T0 ... initial temperature. If None, then estimate
it as 1.2 times the largest cost-function deviation over random points in
the box-shaped region specified by the `lower, upper` input parameters." but
the code says "self.T0 = (fmax-fmin)*1.5"
Would you be willing to enlarge the references for SA to include some the
references at Simulated Annealing (SA) for Mathematical Optimization
(http://rlucente.blogspot.com/2014/09/simulated-annealing-sa-for-mathematica
l.html).
Is it possible to create an example where an end user could pass in a custom
schedule to the simulated annealing code?
>comment on the corresponding changeset on github
How do I execute on this?
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Today's Topics:
1. Re: scipy.optimize.anneal - deprecation (Derek Homeier)
2. Re: scipy.optimize.anneal - deprecation (Charles R Harris)
3. Re: scipy.optimize.anneal - deprecation (Andrew Nelson)
4. Re: scipy.optimize.anneal - deprecation (Andrew Nelson)
----------------------------------------------------------------------
Message: 1
Date: Sun, 12 Oct 2014 21:40:33 +0200
From: Derek Homeier <derek at astro.physik.uni-goettingen.de>
Subject: Re: [SciPy-Dev] scipy.optimize.anneal - deprecation
To: SciPy Developers List <scipy-dev at scipy.org>
Message-ID:
<D93748DA-C79D-469F-A6CC-B401D8F81321 at astro.physik.uni-goettingen.de>
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Hi Robert,
On 12 Oct 2014, at 12:03 am, Robert Lucente - Pipeline
<rlucente at pipeline.com> wrote:
> Did not hear back. Not sure how to interpret that. Would really like
> to
know why anneal was deprecated and why recommend basin hopping which won?t
apply for discrete optimization. I realize that simulated annealing requires
a lot of tweeking.
>
I?d think this should be the right forum to bring up this issue; the idea to
replace anneal with basin hopping seems to have been originally brought up
in this thread
http://mail.scipy.org/pipermail/scipy-dev/2012-October/018032.html
which also discusses some of the former?s perceived shortcomings, but I
don?t know how the decision eventually emerged.
As another option you might perhaps comment on the corresponding changeset
on github and try to start a discussion there.
HTH
Derek
------------------------------
Message: 2
Date: Sun, 12 Oct 2014 17:27:07 -0600
From: Charles R Harris <charlesr.harris at gmail.com>
Subject: Re: [SciPy-Dev] scipy.optimize.anneal - deprecation
To: SciPy Developers List <scipy-dev at scipy.org>
Message-ID:
<CAB6mnx+mBFTNfX44dD+Egbatd8mv716KBsWx74g8iee1Fq4mJg at mail.gmail.com>
Content-Type: text/plain; charset="utf-8"
On Sun, Oct 12, 2014 at 1:40 PM, Derek Homeier <
derek at astro.physik.uni-goettingen.de> wrote:
> Hi Robert,
>
> On 12 Oct 2014, at 12:03 am, Robert Lucente - Pipeline <
> rlucente at pipeline.com> wrote:
>
> > Did not hear back. Not sure how to interpret that. Would really like
> > to
> know why anneal was deprecated and why recommend basin hopping which
> won?t apply for discrete optimization. I realize that simulated
> annealing requires a lot of tweeking.
> >
> I?d think this should be the right forum to bring up this issue; the
> idea to replace anneal with basin hopping seems to have been
> originally brought up in this thread
> http://mail.scipy.org/pipermail/scipy-dev/2012-October/018032.html
> which also discusses some of the former?s perceived shortcomings, but
> I don?t know how the decision eventually emerged.
> As another option you might perhaps comment on the corresponding
> changeset on github and try to start a discussion there.
>
>
Looking at the tests at
http://infinity77.net/global_optimization/multidimensional.html the scipy
version of simulated annealing, SIMANN, performs horribly. However, ANA
seems to do pretty well. So the problem with scipy seems to have been a poor
version of the algorithm and probably we should just fix that.
Chuck
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Message: 3
Date: Mon, 13 Oct 2014 10:37:14 +1100
From: Andrew Nelson <andyfaff at gmail.com>
Subject: Re: [SciPy-Dev] scipy.optimize.anneal - deprecation
To: SciPy Developers List <scipy-dev at scipy.org>
Message-ID:
<CAAbtOZdUJtDeM22GZW1GaqjPLB49Da6GD3fXvNVJaddt5B1WPg at mail.gmail.com>
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On 13 October 201
>
> Looking at the tests at
> http://infinity77.net/global_optimization/multidimensional.html the
> scipy version of simulated annealing, SIMANN, performs horribly.
> However, ANA seems to do pretty well. So the problem with scipy seems
> to have been a poor version of the algorithm and probably we should
> just
fix that.
>
> Chuck
>
Andrea Gavana kindly made the code to the benchmark suite available. I'm
modifying to a form for inclusion into scipy:
https://github.com/andyfaff/scipy/tree/go_benchmark/scipy/optimize/benchmark
s.
As we speak I'm running the test optimization functions (I added a few and
modified some) for basinhopping, differential_evolution and anneal.
I'll put these up in a Gist in the next day or so.
--
_____________________________________
Dr. Andrew Nelson
_____________________________________
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Message: 4
Date: Mon, 13 Oct 2014 16:17:09 +1100
From: Andrew Nelson <andyfaff at gmail.com>
Subject: Re: [SciPy-Dev] scipy.optimize.anneal - deprecation
To: SciPy Developers List <scipy-dev at scipy.org>
Message-ID:
<CAAbtOZe3wPgf-iye-LrOz6TdBkCXA=QeiuAhigsd_HrWbmEBtw at mail.gmail.com>
Content-Type: text/plain; charset="utf-8"
On 13 October 2014 10:37, Andrew Nelson <andyfaff at gmail.com> wrote:
> On 13 October 201
>>
>> Looking at the tests at
>> http://infinity77.net/global_optimization/multidimensional.html the
>> scipy version of simulated annealing, SIMANN, performs horribly.
>> However, ANA seems to do pretty well. So the problem with scipy seems
>> to have been
a
>> poor version of the algorithm and probably we should just fix that.
>>
>> Chuck
>>
>
> Andrea Gavana kindly made the code to the benchmark suite available.
> I'm modifying to a form for inclusion into scipy:
>
https://github.com/andyfaff/scipy/tree/go_benchmark/scipy/optimize/benchmark
s.
> As we speak I'm running the test optimization functions (I added a few
> and modified some) for basinhopping, differential_evolution and anneal.
> I'll put these up in a Gist in the next day or so.
>
>
As promised, the first run through of the test functions for global
optimizers is at: https://gist.github.com/andyfaff/24c96a3d5dbc7b0272b2.
This was for a total of 150 random starting vectors. There are still some
things to be ironed out, particularly how a success is judged (atol vs rtol,
etc). For example, in the Thurber problem (a NIST regression
standard) a lot of failures are because the minimizer used for polishing
(L-BFGS-B) doesn't seem to be able to take the energy from 5645 to 5642.
The parameters are so close to the optimum solution I'm wondering if it's a
precision problem with the numerical derivatives. I think most of those
fails could be counted as successes.
In any case, I'm not going to comment any further, but will let the numbers
tell their own story. For each problem the percentage of successes is
reported (whether the minimizer found the global minimum), as well as the
mean number of function evaluations (irrespective of whether it was a
success or failure).
regards,
Andrew.
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Message: 2
Date: Tue, 14 Oct 2014 08:53:37 +0100
From: Jacob Stevenson <jstevenson131 at gmail.com>
Subject: Re: [SciPy-Dev] scipy.optimize.anneal - deprecation
To: SciPy Developers List <scipy-dev at scipy.org>
Message-ID: <D8EABE25-A273-4BEC-BE46-83165885C572 at gmail.com>
Content-Type: text/plain; charset="windows-1252"
I wrote the documentation for basin hopping and added the ?smooth? comment.
Basinhopping is a very simple algorithm, it?s essentially just a Monte Carlo
routine with local minimisation. All the hard work is done by the local
minimizer, so it?s performance is only as good as the local minimiser.
Most of the local minimisers in scipy (l-bfgs-b, cg, etc) are designed to
work with smooth functions, so basinhopping will really only work well on
smooth functions if one of those minimisers were used.
I can?t think of a reason that basin hopping wouldn't work on non-smooth
functions if a non-smooth minimiser were used (power, coblya, etc). I have
little direct experience with this so I can?t say for sure. Maybe the
?smooth" restriction in the basin hopping documentation should be removed
> Bechmarks are a tough thing.
Very true. Andrea?s collection of benchmark functions is great
(http://infinity77.net/global_optimization/multidimensional.html), but
almost all of them are low dimensional (2-5 dimensions). I primarily deal
with optimisation problems with greater than 100 dimensions. An
optimisation routine which works well in low dimensions will not necessarily
scale to well to high dimensions.
> My only comment is that smooth and non-smooth should be 2 different
> sets of benchmarks
This is a good idea
Jake
On 14 Oct 2014, at 04:45, Robert Lucente - Pipeline <rlucente at pipeline.com>
wrote:
> Hummm. I think I am missing something fundamental.
>
> The official doco for scipy.optimize.basinhopping
> (http://docs.scipy.org/doc/scipy-0.13.0/reference/generated/scipy.opti
> mize.b
> asinhopping.html) states "Basin-hopping is a stochastic algorithm
> which attempts to find the global minimum of a smooth scalar
> function". The key word to note is smooth. The non-math version of
> smooth is that there are no gaps and no breaks. Also, there are no
> kinks and no corners. For a more in depth explanation of this refer to
> pages 297 - 298 of Optimization Modeling with Spreadsheets, Second
> Edition by Kenneth R. Baker. The math version is that the functions
> are continuous and at least twice continuous differentiable. Please
> note that the second derivative must also be continuous. For a more in
> depth explanation of this refer to pages 11 - 12 of Introduction to
Optimum Design, Third Edition by Jasbir Arora.
>
> What happens when the problem you are dealing w/ is not smooth? You
> can't use basin hopping. For example, a price schedule with a price
> break is a standard example of a non-smooth function. My personal and
> immediate non-smooth problem is placing advertising in available time
slots.
>
> Also, the SciPy lecture notes
> (http://scipy-lectures.github.io/advanced/mathematical_optimization/#s
> mooth-
> and-non-smooth-problems) states "2.7.1.2. Smooth and non-smooth problems
...
> Optimizing smooth functions is easier"
>
> Simulated annealing is not perfect. It does have issues like having a
> lot of knobs to turn.
>
> Bechmarks are a tough thing. My only comment is that smooth and
> non-smooth should be 2 different sets of benchmarks. BTW, I love the
> comment "I got fed up with the current attitude of most
> mathematicians/numerical optimization experts, who tend to demonstrate
> the advantages of an algorithm based on "elapsed time" or "CPU time" or
similar meaningless performance indicators"
>
> Minor nit: I think that there is a disconnect between the code for SA
> and its doco. The doco says "T0 ... initial temperature. If None, then
> estimate it as 1.2 times the largest cost-function deviation over
> random points in the box-shaped region specified by the `lower, upper`
> input parameters." but the code says "self.T0 = (fmax-fmin)*1.5"
>
> Would you be willing to enlarge the references for SA to include some
> the references at Simulated Annealing (SA) for Mathematical
> Optimization
> (http://rlucente.blogspot.com/2014/09/simulated-annealing-sa-for-mathe
> matica
> l.html).
>
> Is it possible to create an example where an end user could pass in a
> custom schedule to the simulated annealing code?
>
>> comment on the corresponding changeset on github
> How do I execute on this?
>
> -----Original Message-----
> From: scipy-dev-bounces at scipy.org [mailto:scipy-dev-bounces at scipy.org]
> On Behalf Of scipy-dev-request at scipy.org
> Sent: Monday, October 13, 2014 1:00 PM
> To: scipy-dev at scipy.org
> Subject: SciPy-Dev Digest, Vol 132, Issue 15
>
> Send SciPy-Dev mailing list submissions to
> scipy-dev at scipy.org
>
> To subscribe or unsubscribe via the World Wide Web, visit
> http://mail.scipy.org/mailman/listinfo/scipy-dev
> or, via email, send a message with subject or body 'help' to
> scipy-dev-request at scipy.org
>
> You can reach the person managing the list at
> scipy-dev-owner at scipy.org
>
> When replying, please edit your Subject line so it is more specific
> than
> "Re: Contents of SciPy-Dev digest..."
>
>
> Today's Topics:
>
> 1. Re: scipy.optimize.anneal - deprecation (Derek Homeier)
> 2. Re: scipy.optimize.anneal - deprecation (Charles R Harris)
> 3. Re: scipy.optimize.anneal - deprecation (Andrew Nelson)
> 4. Re: scipy.optimize.anneal - deprecation (Andrew Nelson)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Sun, 12 Oct 2014 21:40:33 +0200
> From: Derek Homeier <derek at astro.physik.uni-goettingen.de>
> Subject: Re: [SciPy-Dev] scipy.optimize.anneal - deprecation
> To: SciPy Developers List <scipy-dev at scipy.org>
> Message-ID:
>
> <D93748DA-C79D-469F-A6CC-B401D8F81321 at astro.physik.uni-goettingen.de>
> Content-Type: text/plain; charset=windows-1252
>
> Hi Robert,
>
> On 12 Oct 2014, at 12:03 am, Robert Lucente - Pipeline
> <rlucente at pipeline.com> wrote:
>
>> Did not hear back. Not sure how to interpret that. Would really like
>> to
> know why anneal was deprecated and why recommend basin hopping which
> won?t apply for discrete optimization. I realize that simulated
> annealing requires a lot of tweeking.
>>
> I?d think this should be the right forum to bring up this issue; the
> idea to replace anneal with basin hopping seems to have been
> originally brought up in this thread
> http://mail.scipy.org/pipermail/scipy-dev/2012-October/018032.html
> which also discusses some of the former?s perceived shortcomings, but
> I don?t know how the decision eventually emerged.
> As another option you might perhaps comment on the corresponding
> changeset on github and try to start a discussion there.
>
> HTH
> Derek
>
>
>
> ------------------------------
>
> Message: 2
> Date: Sun, 12 Oct 2014 17:27:07 -0600
> From: Charles R Harris <charlesr.harris at gmail.com>
> Subject: Re: [SciPy-Dev] scipy.optimize.anneal - deprecation
> To: SciPy Developers List <scipy-dev at scipy.org>
> Message-ID:
> <CAB6mnx+mBFTNfX44dD+Egbatd8mv716KBsWx74g8iee1Fq4mJg at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> On Sun, Oct 12, 2014 at 1:40 PM, Derek Homeier <
> derek at astro.physik.uni-goettingen.de> wrote:
>
>> Hi Robert,
>>
>> On 12 Oct 2014, at 12:03 am, Robert Lucente - Pipeline <
>> rlucente at pipeline.com> wrote:
>>
>>> Did not hear back. Not sure how to interpret that. Would really like
>>> to
>> know why anneal was deprecated and why recommend basin hopping which
>> won?t apply for discrete optimization. I realize that simulated
>> annealing requires a lot of tweeking.
>>>
>> I?d think this should be the right forum to bring up this issue; the
>> idea to replace anneal with basin hopping seems to have been
>> originally brought up in this thread
>> http://mail.scipy.org/pipermail/scipy-dev/2012-October/018032.html
>> which also discusses some of the former?s perceived shortcomings, but
>> I don?t know how the decision eventually emerged.
>> As another option you might perhaps comment on the corresponding
>> changeset on github and try to start a discussion there.
>>
>>
> Looking at the tests at
> http://infinity77.net/global_optimization/multidimensional.html the
> scipy version of simulated annealing, SIMANN, performs horribly.
> However, ANA seems to do pretty well. So the problem with scipy seems
> to have been a poor version of the algorithm and probably we should just
fix that.
>
> Chuck
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> ------------------------------
>
> Message: 3
> Date: Mon, 13 Oct 2014 10:37:14 +1100
> From: Andrew Nelson <andyfaff at gmail.com>
> Subject: Re: [SciPy-Dev] scipy.optimize.anneal - deprecation
> To: SciPy Developers List <scipy-dev at scipy.org>
> Message-ID:
> <CAAbtOZdUJtDeM22GZW1GaqjPLB49Da6GD3fXvNVJaddt5B1WPg at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> On 13 October 201
>>
>> Looking at the tests at
>> http://infinity77.net/global_optimization/multidimensional.html the
>> scipy version of simulated annealing, SIMANN, performs horribly.
>> However, ANA seems to do pretty well. So the problem with scipy seems
>> to have been a poor version of the algorithm and probably we should
>> just
> fix that.
>>
>> Chuck
>>
>
> Andrea Gavana kindly made the code to the benchmark suite available.
> I'm modifying to a form for inclusion into scipy:
> https://github.com/andyfaff/scipy/tree/go_benchmark/scipy/optimize/ben
> chmark
> s.
> As we speak I'm running the test optimization functions (I added a few
> and modified some) for basinhopping, differential_evolution and anneal.
> I'll put these up in a Gist in the next day or so.
>
>
> --
> _____________________________________
> Dr. Andrew Nelson
>
>
> _____________________________________
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>
> ------------------------------
>
> Message: 4
> Date: Mon, 13 Oct 2014 16:17:09 +1100
> From: Andrew Nelson <andyfaff at gmail.com>
> Subject: Re: [SciPy-Dev] scipy.optimize.anneal - deprecation
> To: SciPy Developers List <scipy-dev at scipy.org>
> Message-ID:
> <CAAbtOZe3wPgf-iye-LrOz6TdBkCXA=QeiuAhigsd_HrWbmEBtw at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> On 13 October 2014 10:37, Andrew Nelson <andyfaff at gmail.com> wrote:
>
>> On 13 October 201
>>>
>>> Looking at the tests at
>>> http://infinity77.net/global_optimization/multidimensional.html the
>>> scipy version of simulated annealing, SIMANN, performs horribly.
>>> However, ANA seems to do pretty well. So the problem with scipy
>>> seems to have been
> a
>>> poor version of the algorithm and probably we should just fix that.
>>>
>>> Chuck
>>>
>>
>> Andrea Gavana kindly made the code to the benchmark suite available.
>> I'm modifying to a form for inclusion into scipy:
>>
> https://github.com/andyfaff/scipy/tree/go_benchmark/scipy/optimize/ben
> chmark
> s.
>> As we speak I'm running the test optimization functions (I added a
>> few and modified some) for basinhopping, differential_evolution and
anneal.
>> I'll put these up in a Gist in the next day or so.
>>
>>
>
> As promised, the first run through of the test functions for global
> optimizers is at: https://gist.github.com/andyfaff/24c96a3d5dbc7b0272b2.
> This was for a total of 150 random starting vectors. There are still
> some things to be ironed out, particularly how a success is judged
> (atol vs rtol, etc). For example, in the Thurber problem (a NIST
> regression
> standard) a lot of failures are because the minimizer used for
> polishing
> (L-BFGS-B) doesn't seem to be able to take the energy from 5645 to 5642.
> The parameters are so close to the optimum solution I'm wondering if
> it's a precision problem with the numerical derivatives. I think most
> of those fails could be counted as successes.
>
> In any case, I'm not going to comment any further, but will let the
> numbers tell their own story. For each problem the percentage of
> successes is reported (whether the minimizer found the global
> minimum), as well as the mean number of function evaluations
> (irrespective of whether it was a success or failure).
>
> regards,
> Andrew.
> -------------- next part -------------- An HTML attachment was
> scrubbed...
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> chment-0001.html
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>
> _______________________________________________
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