#include <hybridsimulatedannealing.hpp>

Inheritance diagram for HybridSimulatedAnnealing< Sampler, Probability, Temperature, Reannealing >:

Collaboration diagram for HybridSimulatedAnnealing< Sampler, Probability, Temperature, Reannealing >:

Public Types
enum	LocalOptimizeScheme { NoLocalOptimize , EveryNewPoint , EveryBestPoint }

enum	ResetScheme { NoResetScheme , ResetToBestPoint , ResetToOrigin }

Public Member Functions
	HybridSimulatedAnnealing (const Sampler &sampler, const Probability &probability, Temperature temperature, const Reannealing &reannealing=ReannealingTrivial(), Real startTemperature=200.0, Real endTemperature=0.01, Size reAnnealSteps=50, ResetScheme resetScheme=ResetToBestPoint, Size resetSteps=150, ext::shared_ptr< OptimizationMethod > localOptimizer=ext::shared_ptr< OptimizationMethod >(), LocalOptimizeScheme optimizeScheme=EveryBestPoint)

EndCriteria::Type	minimize (Problem &P, const EndCriteria &endCriteria) override
	minimize the optimization problem P More...

Public Member Functions inherited from OptimizationMethod
virtual	~OptimizationMethod ()=default

virtual EndCriteria::Type	minimize (Problem &P, const EndCriteria &endCriteria)=0
	minimize the optimization problem P More...

Private Attributes
Sampler	sampler_

Probability	probability_

Temperature	temperature_

Reannealing	reannealing_

Real	startTemperature_

Real	endTemperature_

Size	reAnnealSteps_

ResetScheme	resetScheme_

Size	resetSteps_

ext::shared_ptr< OptimizationMethod >	localOptimizer_

LocalOptimizeScheme	optimizeScheme_

Detailed Description

template<class Sampler, class Probability, class Temperature, class Reannealing = ReannealingTrivial>
class QuantLib::HybridSimulatedAnnealing< Sampler, Probability, Temperature, Reannealing >

Method is fairly straightforward: 1) Sampler provides a probability density (based on current value) for the parameters. Each iteration a new draw is made from it to find a new point 2) Probability determines whether the new point, obtained from Sampler, is accepted or not 3) Temperature is a schedule T(k) for the iteration k, which affects the Sampler and Probability 4) Reannealing is a departure from the traditional Boltzmann Annealing method: it rescales the iteration k independently for each dimension so as to improve convergence

The hybrid in the name is because one can provide it a local optimizer for use whenever any new best point is found or at every accepted point, in which case is used is chose by the user.

Class Sampler must implement the following interface:

void operator()(Array &newPoint, const Array &currentPoint, const Array &temp) const;

QuantLib::Array

1-D array used in linear algebra.

Definition: array.hpp:52

Class Probability must implement the following interface:

bool operator()(Real currentValue, Real newValue, const Array &temp) const;

QuantLib::Real

QL_REAL Real

real number

Definition: types.hpp:50

Class Temperature must implement the following interface:

void operator()(Array &newTemp, const Array &currTemp, const Array &steps) const;

Class Reannealing must implement the following interface:

void operator()(Array & steps, const Array &currentPoint,

Real aCurrentValue, const Array & currTemp) const;

Examples: GlobalOptimizer.cpp.

Definition at line 67 of file hybridsimulatedannealing.hpp.

Member Enumeration Documentation

◆ LocalOptimizeScheme

enum LocalOptimizeScheme

Enumerator
NoLocalOptimize
EveryNewPoint
EveryBestPoint

Definition at line 69 of file hybridsimulatedannealing.hpp.

◆ ResetScheme

enum ResetScheme

Enumerator
NoResetScheme
ResetToBestPoint
ResetToOrigin

Definition at line 74 of file hybridsimulatedannealing.hpp.

Constructor & Destructor Documentation

◆ HybridSimulatedAnnealing()

HybridSimulatedAnnealing	(	const Sampler &	sampler,
		const Probability &	probability,
		Temperature	temperature,
		const Reannealing &	reannealing = `ReannealingTrivial()`,
		Real	startTemperature = `200.0`,
		Real	endTemperature = `0.01`,
		Size	reAnnealSteps = `50`,
		ResetScheme	resetScheme = `ResetToBestPoint`,
		Size	resetSteps = `150`,
		ext::shared_ptr< OptimizationMethod >	localOptimizer = `ext::shared_ptr<OptimizationMethod>()`,
		LocalOptimizeScheme	optimizeScheme = `EveryBestPoint`
	)