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