[rules-users] Monte Carlo and additional Optimisers for OptaPlanner

2013-10-25 Thread sirinath
Hi,

Is it possible to provide more out of the box optimisers and solvers as part
of OptaPlanner.

Also add functionality for simulations (Monte Carlo) which would be a good
addition and fit.

Suminda



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Re: [rules-users] Monte Carlo and additional Optimisers for OptaPlanner

2013-10-25 Thread Geoffrey De Smet

On 25-10-13 12:50, sirinath wrote:
 Hi,

 Is it possible to provide more out of the box optimisers and solvers as part
 of OptaPlanner.
Yes, we're trying to add more every major release.
For 6.1 we 'll probably add the CH's cheapest insertion and regret 
insertion.
If you want to add one yourself, start by looking at 
DefaultLocalSearchSolverPhase.java.

 Also add functionality for simulations (Monte Carlo) which would be a good
 addition and fit.
Simulation support would be great indeed - but the requirements aren't 
clearly definied yet (feedback, examples or use cases welcome).

It's already possible to do simulation + optimization
by doing the simulation inside the score function (for example by 
running a monte carlo simulation)
and doing the optimization with optaplanner.

drools-chance (very experimental currently) has a lot of constructs that 
can help in simulation (bayes stuff etc).

 Suminda



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Re: [rules-users] Monte Carlo and additional Optimisers for OptaPlanner

2013-10-25 Thread sirinath
Where is Drools chance hosted?

Perhaps GA/GP can be a part of this?

Also Monte Carlo.

Maybe the current way to do is awkward? Is this covered in the
documentation?
On 25 Oct 2013 17:54, ge0ffrey [via Drools] 
ml-node+s46999n4026497...@n3.nabble.com wrote:


 On 25-10-13 12:50, sirinath wrote:
  Hi,
 
  Is it possible to provide more out of the box optimisers and solvers as
 part
  of OptaPlanner.
 Yes, we're trying to add more every major release.
 For 6.1 we 'll probably add the CH's cheapest insertion and regret
 insertion.
 If you want to add one yourself, start by looking at
 DefaultLocalSearchSolverPhase.java.
 
  Also add functionality for simulations (Monte Carlo) which would be a
 good
  addition and fit.
 Simulation support would be great indeed - but the requirements aren't
 clearly definied yet (feedback, examples or use cases welcome).

 It's already possible to do simulation + optimization
 by doing the simulation inside the score function (for example by
 running a monte carlo simulation)
 and doing the optimization with optaplanner.

 drools-chance (very experimental currently) has a lot of constructs that
 can help in simulation (bayes stuff etc).

 
  Suminda
 
 
 
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Re: [rules-users] Monte Carlo and additional Optimisers for OptaPlanner

2013-10-25 Thread Geoffrey De Smet


On 25-10-13 16:08, sirinath wrote:


Where is Drools chance hosted?


https://github.com/droolsjbpm/drools-chance


Perhaps GA/GP can be a part of this?


Yes, here's a Genetic Algoritms prototype for OptaPlanner:
  https://github.com/elsam/optaplanner
Results with GA's were poor, but we're going to add it sooner or later.
Here's the relevant issue to add it:
  https://issues.jboss.org/browse/PLANNER-154


Also Monte Carlo.

Maybe the current way to do is awkward? Is this covered in the 
documentation?



simulation isn't covered in the documentation.

What kind of simulation do you want to do?
What's the problem definition?

On 25 Oct 2013 17:54, ge0ffrey [via Drools] [hidden email] 
/user/SendEmail.jtp?type=nodenode=4026499i=0 wrote:



On 25-10-13 12:50, sirinath wrote:
 Hi,

 Is it possible to provide more out of the box optimisers and
solvers as part
 of OptaPlanner.
Yes, we're trying to add more every major release.
For 6.1 we 'll probably add the CH's cheapest insertion and regret
insertion.
If you want to add one yourself, start by looking at
DefaultLocalSearchSolverPhase.java.

 Also add functionality for simulations (Monte Carlo) which would
be a good
 addition and fit.
Simulation support would be great indeed - but the requirements
aren't
clearly definied yet (feedback, examples or use cases welcome).

It's already possible to do simulation + optimization
by doing the simulation inside the score function (for example by
running a monte carlo simulation)
and doing the optimization with optaplanner.

drools-chance (very experimental currently) has a lot of
constructs that
can help in simulation (bayes stuff etc).


 Suminda



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