| PowerAdditiveCooling {xegaPopulation} | R Documentation |
Power additive cooling.
Description
This schedule decreases by a power of the
n (= number of generations) linear fractions
between the starting temperature lF$Temp0
and the final temperature lF$tempN.
Usage
PowerAdditiveCooling(k, lF)
Arguments
k |
Number of steps to discount. |
lF |
Local configuration. |
Details
Temperature is updated at the end of each generation
in the main loop of the genetic algorithm.
lF$Temp0() is the starting temperature.
lF$TempN() is the final temperature.
lF$CoolingPower() is an exponential factor.
lF$Generations() is the number of generations (time).
Value
Temperature at time k.
References
The-Crankshaft Publishing (2023) A Comparison of Cooling Schedules for Simulated Annealing. <https://what-when-how.com/artificial-intelligence/a-comparison-of-cooling-schedules-for-simulated-annealing-artificial-intelligence/>
See Also
Other Cooling:
ExponentialAdditiveCooling(),
ExponentialMultiplicativeCooling(),
LogarithmicMultiplicativeCooling(),
PowerMultiplicativeCooling(),
TrigonometricAdditiveCooling()
Examples
parm<-function(x){function() {return(x)}}
lF<-list(Temp0=parm(100), TempN=parm(10), Generations=parm(50), CoolingPower=parm(2))
PowerAdditiveCooling(0, lF)
PowerAdditiveCooling(2, lF)