xegaPopulation (version 1.0.0.12)

PowerAdditiveCooling: 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)

Value

Temperature at time k.

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).

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)