AI-ParticleSwarmOptimization
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lib/AI/ParticleSwarmOptimization.pm view on Meta::CPAN
-I<-posMax> (if I<-posMax> is negative I<-posMin> should be set more negative).
=item I<-randSeed>: number, optional
Seed for the random number generator. Useful if you want to rerun an
optimization, perhaps for benchmarking or test purposes.
=item I<-randStartVelocity>: boolean, optional
Set true to initialize particles with a random velocity. Otherwise particle
velocity is set to 0 on initalization.
A range based on 1/100th of -I<-posMax> - I<-posMin> is used for the initial
speed in each dimension of the velocity vector if a random start velocity is
used.
=item I<-stallSpeed>: positive number, optional
Speed below which a particle is considered to be stalled and is repositioned to
a new random location with a new initial speed.
By default I<-stallSpeed> is undefined but particles with a speed of 0 will be
repositioned.
=item I<-themWeight>: number, optional
Coefficient determining the influence of the neighbourhod best position on the
next iterations velocity. Defaults to 0.5.
See also I<-inertia> and I<-meWeight>.
=item I<-exitPlateau>: boolean, optional
Set true to have the optimization check for plateaus (regions where the fit
hasn't improved much for a while) during the search. The optimization ends when
a suitable plateau is detected following the burn in period.
Defaults to undefined (option disabled).
=item I<-exitPlateauDP>: number, optional
Specify the number of decimal places to compare between the current fitness
function value and the mean of the previous I<-exitPlateauWindow> values.
Defaults to 10.
=item I<-exitPlateauWindow>: number, optional
Specify the size of the window used to calculate the mean for comparison to
the current output of the fitness function. Correlates to the minimum size of a
plateau needed to end the optimization.
Defaults to 10% of the number of iterations (I<-iterations>).
=item I<-exitPlateauBurnin>: number, optional
Determines how many iterations to run before checking for plateaus.
Defaults to 50% of the number of iterations (I<-iterations>).
=item I<-verbose>: flags, optional
If set to a non-zero value I<-verbose> determines the level of diagnostic print
reporting that is generated during optimization.
The following constants may be bitwise ored together to set logging options:
=over 4
=item * kLogBetter
prints particle details when its fit becomes bebtter than its previous best.
=item * kLogStall
prints particle details when its velocity reaches 0 or falls below the stall
threshold.
=item * kLogIter
Shows the current iteration number.
=item * kLogDetail
Shows additional details for some of the other logging options.
=item * kLogIterDetail
Shorthand for C<kLogIter | kLogIterDetail>
=back
=back
=item B<setParams (%parameters)>
Set or change optimization parameters. See I<-new> above for a description of
the parameters that may be supplied.
=item B<init ()>
Reinitialize the optimization. B<init ()> will be called during the first call
to B<optimize ()> if it hasn't already been called.
=item B<optimize ()>
Runs the minimization optimization. Returns the fit value of the best fit
found. The best possible fit is negative infinity.
B<optimize ()> may be called repeatedly to continue the fitting process. The fit
processing on each subsequent call will continue from where the last call left
off.
=item B<getParticleState ()>
Returns the vector of position
=item B<getBestParticles ([$n])>
Takes an optional count.
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