This schedule decreases in proportion to the
cosine of the temperature cycle in
lF$Generations() (= number of generations) fractions
between the starting temperature lF$Temp0()
and the final temperature lF$TempN().
Usage
TrigonometricAdditiveCooling(k, lF)
Value
Temperature at time k.
Arguments
k
Number of steps (time).
lF
Local configuration.
Details
Temperature is updated at the end of each generation
in the main loop of the genetic algorithm.
lF$Temp0() is the starting temperature.
lF$TempN() is the final temperature.
lF$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(),
PowerAdditiveCooling(),
PowerMultiplicativeCooling()