ExponentialMultiplicativeCooling {xegaPopulation}

Exponential multiplicative cooling.

Description

The temperature at time k is the net present value of the starting temperature. The discount factor is lF$Alpha(). lF$Alpha() should be in [0, 1].

Usage

ExponentialMultiplicativeCooling(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$Temp0() is the starting temperature. lF$Alpha() is the discount factor.

Value

Temperature at time k.

References

Kirkpatrick, S., Gelatt, C. D. J, and Vecchi, M. P. (1983): Optimization by Simulated Annealing. Science, 220(4598): 671-680. <doi:10.1126/science.220.4598.671>

See Also

Other Cooling: ExponentialAdditiveCooling(), LogarithmicMultiplicativeCooling(), PowerAdditiveCooling(), PowerMultiplicativeCooling(), TrigonometricAdditiveCooling()

Examples

parm<-function(x){function() {return(x)}}
lF<-list(Temp0=parm(100), Alpha=parm(0.99))
ExponentialMultiplicativeCooling(0, lF)
ExponentialMultiplicativeCooling(2, lF)