QuantLib_HybridSimulatedAnnealing man page

HybridSimulatedAnnealing< Sampler, Probability, Temperature, Reannealing >

Synopsis

`#include <ql/experimental/math/hybridsimulatedannealing.hpp>`

Inherits OptimizationMethod.

Public Types

enum LocalOptimizeScheme { NoLocalOptimize, EveryNewPoint, EveryBestPoint }
enum ResetScheme { NoResetScheme, ResetToBestPoint, ResetToOrigin }

Public Member Functions

HybridSimulatedAnnealing (const Sampler &sampler, const Probability &probability, const Temperature &temperature, const Reannealing &reannealing=ReannealingTrivial(), Real startTemperature=200.0, Real endTemperature=0.01, Size reAnnealSteps=50, ResetScheme resetScheme=ResetToBestPoint, Size resetSteps=150, boost::shared_ptr< OptimizationMethod > localOptimizer=boost::shared_ptr< OptimizationMethod >(), LocalOptimizeScheme optimizeScheme=EveryBestPoint)
EndCriteria::Type minimize (Problem &P, const EndCriteria &endCriteria)
minimize the optimization problem P

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;`

Class Probability must implement the following interface:

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

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;```

Author

Generated automatically by Doxygen for QuantLib from the source code.

Referenced By

The man page HybridSimulatedAnnealing(3) is an alias of QuantLib_HybridSimulatedAnnealing(3).

Wed Feb 7 2018 Version 1.10.1 QuantLib