Search
Preparing search index...
The search index is not available
quantlib.js
Options
All
Public
Public/Protected
All
Inherited
Externals
Only exported
Menu
Globals
"ql/experimental/math/hybridsimulatedannealing"
MirrorGaussianSimulatedAnnealing
Class MirrorGaussianSimulatedAnnealing
Hierarchy
HybridSimulatedAnnealing
MirrorGaussianSimulatedAnnealing
Index
Enumerations
Local
Optimize
Scheme
Reset
Scheme
Constructors
constructor
Accessors
is
Disposed
Methods
dispose
minimize
Constructors
constructor
new
Mirror
Gaussian
Simulated
Annealing
(
Sampler
:
any
, Probability
:
any
, Temperature
:
any
, Reannealing
?:
any
, startTemperature
?:
Real
, endTemperature
?:
Real
, reAnnealSteps
?:
Size
, resetScheme
?:
ResetScheme
, resetSteps
?:
Size
, localOptimizer
?:
OptimizationMethod
, optimizeScheme
?:
LocalOptimizeScheme
)
:
MirrorGaussianSimulatedAnnealing
Parameters
Sampler:
any
Probability:
any
Temperature:
any
Default value
Reannealing:
any
= new ReannealingTrivial()
Default value
startTemperature:
Real
= 200
Default value
endTemperature:
Real
= 0.01
Default value
reAnnealSteps:
Size
= 50
Default value
resetScheme:
ResetScheme
= HybridSimulatedAnnealing.ResetScheme.ResetToBestPoint
Default value
resetSteps:
Size
= 150
Default value
localOptimizer:
OptimizationMethod
= new OptimizationMethod()
Default value
optimizeScheme:
LocalOptimizeScheme
= HybridSimulatedAnnealing.LocalOptimizeScheme.EveryBestPoint
Returns
MirrorGaussianSimulatedAnnealing
Accessors
is
Disposed
get
isDisposed
(
)
:
boolean
Returns
boolean
Methods
dispose
dispose
(
)
:
void
Returns
void
minimize
minimize
(
P
:
Problem
, endCriteria
:
EndCriteria
)
:
Type
minimize the optimization problem P
Parameters
P:
Problem
endCriteria:
EndCriteria
Returns
Type
Globals
"ql/experimental/math/hybridsimulatedannealing"
Gaussian
Simulated
Annealing
Gaussian
Simulated
ReAnnealing
Hybrid
Simulated
Annealing
Log
Normal
Simulated
Annealing
Mirror
Gaussian
Simulated
Annealing
Local
Optimize
Scheme
Reset
Scheme
constructor
is
Disposed
dispose
minimize
Very
Fast
Simulated
Annealing
Very
Fast
Simulated
ReAnnealing
minimize the optimization problem P