Numerical Optimizer (Solver) for LTSpice

I have written a numerical optimizer (solver) for LTSpice. It automatically adjusts component values to meet circuit performance targets you set. For example maximum power output and minimum supply current. It uses a fast evolutionary algorithm to get good results quickly. You can get good results in anything from 5 minutes to a few hours depending on the complexity of the circuit. It is much faster and better than using any of the genetic algorithms available or the Simplex method.
Anyway I have provided a free trial usable until 5 August with a 3000 iteration limit. I am thinking about providing a 3 month trial with an iteration limit of about 500 afterwards.
You can try it here:
http://www.evospice.site88.net/evospice/evospice.html
Best Regards,
Sean O'Connor

 

[Mike]

bitterlemon40@yahoo.ie wrote:

I have written a numerical optimizer (solver) for LTSpice. It
automatically adjusts component values to meet circuit performance
targets you set. For example maximum power output and minimum supply
current. It uses a fast evolutionary algorithm to get good results
quickly. You can get good results in anything from 5 minutes to a few
hours depending on the complexity of the circuit. It is much faster
and better than using any of the genetic algorithms available or the
Simplex method. Anyway I have provided a free trial usable until 5
August with a 3000 iteration limit. I am thinking about providing a 3
month trial with an iteration limit of about 500 afterwards. You can
try it here: http://www.evospice.site88.net/evospice/evospice.html
Best Regards,
Sean O'Connor

Is this the same one you annnounced in the LTspice forum last Saturday?

If so, Helmut says it is slow, cannot optimize multiple variables, and is
at least 10 times over-prized.

http://tech.groups.yahoo.com/group/LTspice/message/59190?l=1

 

[Jim Thompson]

On Tue, 24 Jul 2012 01:17:17 GMT, Mike <spam@me.not> wrote:

bitterlemon40@yahoo.ie wrote:

I have written a numerical optimizer (solver) for LTSpice. It
automatically adjusts component values to meet circuit performance
targets you set. For example maximum power output and minimum supply
current. It uses a fast evolutionary algorithm to get good results
quickly. You can get good results in anything from 5 minutes to a few
hours depending on the complexity of the circuit. It is much faster
and better than using any of the genetic algorithms available or the
Simplex method. Anyway I have provided a free trial usable until 5
August with a 3000 iteration limit. I am thinking about providing a 3
month trial with an iteration limit of about 500 afterwards. You can
try it here: http://www.evospice.site88.net/evospice/evospice.html
Best Regards,
Sean O'Connor

Is this the same one you annnounced in the LTspice forum last Saturday?

If so, Helmut says it is slow, cannot optimize multiple variables, and is
at least 10 times over-prized.

http://tech.groups.yahoo.com/group/LTspice/message/59190?l=1

Sounds to me like fast evolutionary algorithmic bullshit

Plus I feel any circuit subject to such a tool wouldn't qualify as
having been properly designed in the first place.

...Jim Thompson
--
| James E.Thompson, CTO | mens |
| Analog Innovations, Inc. | et |
| Analog/Mixed-Signal ASIC's and Discrete Systems | manus |
| Phoenix, Arizona 85048 Skype: Contacts Only | |
| Voice480)460-2350 Fax: Available upon request | Brass Rat |
| E-mail Icon at http://www.analog-innovations.com | 1962 |

I love to cook with wine. Sometimes I even put it in the food.

 

[Phil Hobbs]

bitterlemon40@yahoo.ie wrote:

I have written a numerical optimizer (solver) for LTSpice. It automatically adjusts component values to meet circuit performance targets you set. For example maximum power output and minimum supply current. It uses a fast evolutionary algorithm to get good results quickly. You can get good results in anything from 5 minutes to a few hours depending on the complexity of the circuit. It is much faster and better than using any of the genetic algorithms available or the Simplex method.
Anyway I have provided a free trial usable until 5 August with a 3000 iteration limit. I am thinking about providing a 3 month trial with an iteration limit of about 500 afterwards.
You can try it here:
http://www.evospice.site88.net/evospice/evospice.html
Best Regards,
Sean O'Connor

Is there a manual for it? If it's any good, $50 is a gift. If not,
it's too expensive.

Cheers

Phil Hobbs

--
Dr Philip C D Hobbs
Principal Consultant
ElectroOptical Innovations LLC
Optics, Electro-optics, Photonics, Analog Electronics

160 North State Road #203
Briarcliff Manor NY 10510
845-480-2058

hobbs at electrooptical dot net
http://electrooptical.net

 

[Mike]

bitterlemon40@yahoo.ie wrote:

Hi Mike,
Yes that is right. Unfortunately he could not get it to work right. I
have updated the documentation to make it easier to understand. It is
very simple to set up. I will provide some example files in the next
few weeks which will make it even easier to understand. Best Regards,
Sean O'Connor

Can you run some time comparisons on different circuit complexity between
your program and the solver Helmut referred to? Any differences in the
results should be resolved.

Also include on a BandGap as suggested by Jim.

 

Worried? While I agree that AI has been a big flop in general I think you had better know that Evolutionary Algorithms are starting to show human competitive results. There is a lot of 'Robot' trading on the financial markets for example. There are human competitive results in engineering (antennas for example) and science (drug design). Do some of your designers spend entire days playing around component values trying to find some elusive sweet-spot? That time wasting can be stopped, the number of designers can be reduced. If you equate evolutionary algorithms to animal droppings then your company will be left behind while others take your business.

 

Hi Mike,
Yes that is right. Unfortunately he could not get it to work right. I have updated the documentation to make it easier to understand. It is very simple to set up. I will provide some example files in the next few weeks which will make it even easier to understand.
Best Regards,
Sean O'Connor

 

[Jeff Liebermann]

On Mon, 23 Jul 2012 18:24:19 -0700, Jim Thompson
<To-Email-Use-The-Envelope-Icon@On-My-Web-Site.com> wrote:

Plus I feel any circuit subject to such a tool wouldn't qualify as
having been properly designed in the first place.
...Jim Thompson

I don't know about circuit design, but in the area of antenna design,
the optimizer is a key part of the design process. With circuit
design, there may be a few parts that affect each other. In antenna
design, everything affects everything else, making every length,
spacing, and value a compromise between the various parameters (gain,
bandwidth, vswr, pattern, etc). For example, in 4NEC2, I set the
target values, establish weighing factors for the lengths and spacings
that will change, and let the program grind most of the night trying
to find an optimal compromise. I could probably get close doing all
this manually, but it's so much better and easier using an optimizer.
At the least, it allows mediocre antenna designers (like me) to do
better than mediocre work. I suspect that might also apply to
optimizers in circuit design.

"Antenna simulation tutorial 3 - 4NEC2 optimizer and impedance
matching"
<http://www.youtube.com/watch?v=kYy6Yur127A>

Examples of some of my antennas (not all are mine), most of which were
fed to an optimizer for the final tweaks:
<http://802.11junk.com/jeffl/antennas/>
<http://802.11junk.com/jeffl/antennas/index2.html>

--
# Jeff Liebermann 150 Felker St #D Santa Cruz CA 95060
# 831-336-2558
# http://802.11junk.com jeffl@cruzio.com
# http://www.LearnByDestroying.com AE6KS

 

There is only the short built-in help file at the moment. Most of the complexity is in setting up the measurements (.measure, .meas) you require within LTSpice itself. The LTSpice help file is a bit Spartan in words about how exactly to do measurements but you can figure it out anyway.
Regards,
Sean O'Connor

 

[bitrex]

On 7/23/2012 8:59 PM, bitterlemon40@yahoo.ie wrote:

I have written a numerical optimizer (solver) for LTSpice. It automatically adjusts component values to meet circuit performance targets you set. For example maximum power output and minimum supply current. It uses a fast evolutionary algorithm to get good results quickly. You can get good results in anything from 5 minutes to a few hours depending on the complexity of the circuit. It is much faster and better than using any of the genetic algorithms available or the Simplex method.
Anyway I have provided a free trial usable until 5 August with a 3000 iteration limit. I am thinking about providing a 3 month trial with an iteration limit of about 500 afterwards.
You can try it here:
http://www.evospice.site88.net/evospice/evospice.html
Best Regards,
Sean O'Connor

Looks interesting - I have been playing with similar ideas, though not
via LTSpice. I'm a bit more interested in topology evolution than
parameter optimization, though it seems to be a somewhat more difficult
problem to adapt to GA methods. Do you have plans for your software to
be able to match AC analysis parameters as well?

I'll certainly give it a try.

 

[Nico Coesel]

bitterlemon40@yahoo.ie wrote:

Worried? While I agree that AI has been a big flop in general I think you h=
ad better know that Evolutionary Algorithms are starting to show human comp=

You mean genetic algorithms? Those are not suitable for problems with
only one solution.

etitive results. There is a lot of 'Robot' trading on the financial market=
s for example. There are human competitive results in engineering (antennas=
for example) and science (drug design). Do some of your designers spend e=
ntire days playing around component values trying to find some elusive swee=

Wouldn't it be easier to calculate the proper values and include their
real life tolerances? Can you give one practical example where your
algorithm would solve a problem quicker than a good EE could?

--
Failure does not prove something is impossible, failure simply
indicates you are not using the right tools...
nico@nctdevpuntnl (punt=.)
--------------------------------------------------------------

 

[Phil Hobbs]

On 07/24/2012 12:17 AM, Jeff Liebermann wrote:

On Mon, 23 Jul 2012 18:24:19 -0700, Jim Thompson
To-Email-Use-The-Envelope-Icon@On-My-Web-Site.com> wrote:

Plus I feel any circuit subject to such a tool wouldn't qualify as
having been properly designed in the first place.
...Jim Thompson

I don't know about circuit design, but in the area of antenna design,
the optimizer is a key part of the design process. With circuit
design, there may be a few parts that affect each other. In antenna
design, everything affects everything else, making every length,
spacing, and value a compromise between the various parameters (gain,
bandwidth, vswr, pattern, etc). For example, in 4NEC2, I set the
target values, establish weighing factors for the lengths and spacings
that will change, and let the program grind most of the night trying
to find an optimal compromise. I could probably get close doing all
this manually, but it's so much better and easier using an optimizer.
At the least, it allows mediocre antenna designers (like me) to do
better than mediocre work. I suspect that might also apply to
optimizers in circuit design.

"Antenna simulation tutorial 3 - 4NEC2 optimizer and impedance
matching"
http://www.youtube.com/watch?v=kYy6Yur127A

Examples of some of my antennas (not all are mine), most of which were
fed to an optimizer for the final tweaks:
http://802.11junk.com/jeffl/antennas/
http://802.11junk.com/jeffl/antennas/index2.html

My EM simulator code uses the Nelder-Mead downhill simplex method to
optimize over completely arbitrary user-defined parameters. I couldn't
have done my infrared antenna gizmos without it--the materials don't
have nice simple metal and dielectric behaviour at 200 THz.

I thought about using a response-surface optimizer, but FDTD results
aren't continuous functions of the parameters in general, and
Nelder-Mead does a lot better at that than more sophisticated algorithms
do. You just have to restart it a few times to make sure it hasn't got
wedged, which it sometimes does.

There are a couple of things I could use a SPICE optimizer for, but if I
were writing it myself, I'd probably just use Nelder-Mead or simulated
annealing again, because I really like being able to use arbitrary
parameters.

Genetic algorithms can be pretty useful for some things, especially
antennas, but despite the cool name, they're just another wrench in the
toolbox.

Cheers

Phil Hobbs

--
Dr Philip C D Hobbs
Principal Consultant
ElectroOptical Innovations LLC
Optics, Electro-optics, Photonics, Analog Electronics

160 North State Road #203
Briarcliff Manor NY 10510
845-480-2058

hobbs at electrooptical dot net
http://electrooptical.net

 

[Martin Brown]

On 24/07/2012 13:57, Nico Coesel wrote:

bitterlemon40@yahoo.ie wrote:

Worried? While I agree that AI has been a big flop in general I think you h=
ad better know that Evolutionary Algorithms are starting to show human comp=

You mean genetic algorithms? Those are not suitable for problems with
only one solution.

There may be better algorithms where a unique global maximum is
guaranteed for example conjugate gradients, but that doesn't prevent
genetic algorithms or simulated annealing from working it just means
they are not the quickest way to a solution. Methods that exploit a well
defined gradient structure are almost always preferable.

etitive results. There is a lot of 'Robot' trading on the financial market=

I would not use that as a favourable example. High speed computer based
trading is responsible for most of the insane market volatility these
days - that and herd instinct. It is only a matter of time before some
idiot crashes a major bank into the ground with a sophisticated double
or quits bet that fails many hundreds of times in a millisecond.
Last one was in 2010:

http://www.thestreet.com/story/10749261/1/did-trading-error-worsen-market-plunge.html

s for example. There are human competitive results in engineering (antennas=
for example) and science (drug design). Do some of your designers spend e=
ntire days playing around component values trying to find some elusive swee=

Wouldn't it be easier to calculate the proper values and include their
real life tolerances? Can you give one practical example where your
algorithm would solve a problem quicker than a good EE could?

Antenna design would be an obvious example where everything is a design
tradeoff and multiple optima exist. You do have to worry about a design
with such elusive sweet spots that an engineer cannot see how to
optimise it without computer aid.

The advantage of a computer optimisation algorithm is that it prevents
poor engineers from cluelessly altering parameters and never making
progress. A classic case would be where an optimum occurs in a steep
valley at 45 degrees to two of the available tuning parameters.

The same is true of focussing ion optics (where simplex is good enough)
very often pairs (or more) of classical potentiometer controls have to
be moved together in some well defined ratio. Computer optimisation wins
because after a while it finds the eigenvectors of the matrix.

I suspect the future lies with engineers defining the topology of a
circuit and optimising tools adjusting things to work best.

Where "best" is some subjective mixture of minimum current, cost to
build and maximum efficiency.

--
Regards,
Martin Brown

 

[Jim Thompson]

On Tue, 24 Jul 2012 12:57:09 GMT, nico@puntnl.niks (Nico Coesel)
wrote:

bitterlemon40@yahoo.ie wrote:

Worried? While I agree that AI has been a big flop in general I think you h=
ad better know that Evolutionary Algorithms are starting to show human comp=

You mean genetic algorithms? Those are not suitable for problems with
only one solution.

etitive results. There is a lot of 'Robot' trading on the financial market=
s for example. There are human competitive results in engineering (antennas=
for example) and science (drug design). Do some of your designers spend e=
ntire days playing around component values trying to find some elusive swee=

Wouldn't it be easier to calculate the proper values and include their
real life tolerances? Can you give one practical example where your
algorithm would solve a problem quicker than a good EE could?

My point exactly. I _so_ much enjoyed the "optimization" of my
bandgap even if my derision and laughter directed at the manager cost
me a project.

...Jim Thompson
--
| James E.Thompson, CTO | mens |
| Analog Innovations, Inc. | et |
| Analog/Mixed-Signal ASIC's and Discrete Systems | manus |
| Phoenix, Arizona 85048 Skype: Contacts Only | |
| Voice480)460-2350 Fax: Available upon request | Brass Rat |
| E-mail Icon at http://www.analog-innovations.com | 1962 |

I love to cook with wine. Sometimes I even put it in the food.

 

[Jim Thompson]

On Tue, 24 Jul 2012 15:23:56 +0100, Martin Brown
<|||newspam|||@nezumi.demon.co.uk> wrote:

On 24/07/2012 13:57, Nico Coesel wrote:
bitterlemon40@yahoo.ie wrote:

Worried? While I agree that AI has been a big flop in general I think you h=
ad better know that Evolutionary Algorithms are starting to show human comp=

You mean genetic algorithms? Those are not suitable for problems with
only one solution.

There may be better algorithms where a unique global maximum is
guaranteed for example conjugate gradients, but that doesn't prevent
genetic algorithms or simulated annealing from working it just means
they are not the quickest way to a solution. Methods that exploit a well
defined gradient structure are almost always preferable.

etitive results. There is a lot of 'Robot' trading on the financial market=

I would not use that as a favourable example. High speed computer based
trading is responsible for most of the insane market volatility these
days - that and herd instinct. It is only a matter of time before some
idiot crashes a major bank into the ground with a sophisticated double
or quits bet that fails many hundreds of times in a millisecond.
Last one was in 2010:

http://www.thestreet.com/story/10749261/1/did-trading-error-worsen-market-plunge.html

s for example. There are human competitive results in engineering (antennas=
for example) and science (drug design). Do some of your designers spend e=
ntire days playing around component values trying to find some elusive swee=

Wouldn't it be easier to calculate the proper values and include their
real life tolerances? Can you give one practical example where your
algorithm would solve a problem quicker than a good EE could?

Antenna design would be an obvious example where everything is a design
tradeoff and multiple optima exist. You do have to worry about a design
with such elusive sweet spots that an engineer cannot see how to
optimise it without computer aid.

Unless you're Lan Jen Chu, one of my Professors

The advantage of a computer optimisation algorithm is that it prevents
poor engineers from cluelessly altering parameters and never making
progress. A classic case would be where an optimum occurs in a steep
valley at 45 degrees to two of the available tuning parameters.

The same is true of focussing ion optics (where simplex is good enough)
very often pairs (or more) of classical potentiometer controls have to
be moved together in some well defined ratio. Computer optimisation wins
because after a while it finds the eigenvectors of the matrix.

I suspect the future lies with engineers defining the topology of a
circuit and optimising tools adjusting things to work best.

Where "best" is some subjective mixture of minimum current, cost to
build and maximum efficiency.

Most decent Spice simulators can do at least two dimensional
parameterization (and thus search for an optimum) without any
particular effort on the user's part.

But more degrees of freedom requires cleverness.

...Jim Thompson
--
| James E.Thompson, CTO | mens |
| Analog Innovations, Inc. | et |
| Analog/Mixed-Signal ASIC's and Discrete Systems | manus |
| Phoenix, Arizona 85048 Skype: Contacts Only | |
| Voice480)460-2350 Fax: Available upon request | Brass Rat |
| E-mail Icon at http://www.analog-innovations.com | 1962 |

I love to cook with wine. Sometimes I even put it in the food.

 

[Charlie E.]

On Mon, 23 Jul 2012 21:17:54 -0700, Jeff Liebermann <jeffl@cruzio.com>
wrote:

On Mon, 23 Jul 2012 18:24:19 -0700, Jim Thompson
To-Email-Use-The-Envelope-Icon@On-My-Web-Site.com> wrote:

Plus I feel any circuit subject to such a tool wouldn't qualify as
having been properly designed in the first place.
...Jim Thompson

I don't know about circuit design, but in the area of antenna design,
the optimizer is a key part of the design process. With circuit
design, there may be a few parts that affect each other. In antenna
design, everything affects everything else, making every length,
spacing, and value a compromise between the various parameters (gain,
bandwidth, vswr, pattern, etc). For example, in 4NEC2, I set the
target values, establish weighing factors for the lengths and spacings
that will change, and let the program grind most of the night trying
to find an optimal compromise. I could probably get close doing all
this manually, but it's so much better and easier using an optimizer.
At the least, it allows mediocre antenna designers (like me) to do
better than mediocre work. I suspect that might also apply to
optimizers in circuit design.

"Antenna simulation tutorial 3 - 4NEC2 optimizer and impedance
matching"
http://www.youtube.com/watch?v=kYy6Yur127A

Examples of some of my antennas (not all are mine), most of which were
fed to an optimizer for the final tweaks:
http://802.11junk.com/jeffl/antennas/
http://802.11junk.com/jeffl/antennas/index2.html

Back in the dark ages, we were using Touchstone in our MW circuits
class. Several of the guys had found the optimiser in it, and they
would set it up and run it all night to try and find the best
solutions. Me? I could never bother with it. Instead, I found there
was also a parameter 'tune' function where you adjust a parameter, and
then run a simulation and look at the graph of the result.

I would set up almost all my values as parameters, and then Play! You
take this length or that width, and start playing with the values, and
then watch what the output does. Extremely educational, as you could
see the effects in almost real time, giving you a great 'feel' for
what values did what.

Once I had a handle on it, I could optimize a filter in a few minutes,
just adjusting first this parameter, and then this one.

The guys using the optimiser? My favorite was the guy that was
programming for a band pass filter, and forgot to put in the stop
bands. His result? A single transmission line... ;-)

Charlie

 

[Fred Abse]

On Mon, 23 Jul 2012 17:59:32 -0700, bitterlemon40 wrote:

I have written a numerical optimizer (solver) for LTSpice.

Does it run under Wine, in Linux?

--
"For a successful technology, reality must take precedence
over public relations, for nature cannot be fooled."
(Richard Feynman)