Hi Thomas,
Thanks for the hints.
> thanks for the sample code.
>
> Something that may be helpful for you:
>
> You compute the relative action frequencies for each resource and then add
> a constraint that they have to be equal to the expected probabilities for
> this action in total. This is quite a hard constraint, try to relax it like
> that:
I tried that out and it leads to the same solution, but also the runtime
doesn't change.
> Another observation that I have made, the resources array does contain a
> lot of zeros, but when creating the constraint that each resource must have
> one action assigned this is not taken into account (my understanding is
> that when in the resource array the corresponding entry is 0, this action
> can not be assigned to this resource), so I added also this:
>
> if (resources[bucket][action] != 0.0) {
> constraintValuesAction[currentIndex] = 1;
> }
>
> this means only the actions that are available for this resource are used.
This is rather a matter of data representation - the assumption that the action
cannot be assigned to a resource if the value is 0 is not true, so I cannot do
this optimization.
Thanks anyway for the help and I guess I just wait for the 4.0 release to be
able to get the result after x iterations. One minor remark as I think you are
part of the developing team:
The type "GoalType" is currently in the package nonlinear.scalar, but also used
by linear optimizations. Maybe its a bit cleaner to move it to the optim
package.
Cheers,
Thorsten
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