SimulatedAnnealing< RNG > Class Template Reference

Simulated Annealing. More...

#include <ql/math/optimization/simulatedannealing.hpp>

Inheritance diagram for SimulatedAnnealing< RNG >:

Public Types
enum	Scheme { ConstantFactor , ConstantBudget }

Public Member Functions
	SimulatedAnnealing (const Real lambda, const Real T0, const Real epsilon, const Size m, const RNG &rng=RNG())
	SimulatedAnnealing (const Real lambda, const Real T0, const Size K, const Real alpha, const RNG &rng=RNG())
EndCriteria::Type	minimize (Problem &P, const EndCriteria &ec) override
	minimize the optimization problem P

Detailed Description

template<class RNG = MersenneTwisterUniformRng>
class QuantLib::SimulatedAnnealing< RNG >

Simulated Annealing.

Class RNG must implement the following interface:

RNG::sample_type RNG::next() const;

Examples

GlobalOptimizer.cpp.

Constructor & Destructor Documentation

SimulatedAnnealing() [1/2]

template<class RNG = MersenneTwisterUniformRng>

SimulatedAnnealing	(	const Real	lambda,
		const Real	T0,
		const Real	epsilon,
		const Size	m,
		const RNG &	rng = RNG() )

reduce temperature T by a factor of \( (1-\epsilon) \) after m moves

SimulatedAnnealing() [2/2]

template<class RNG = MersenneTwisterUniformRng>

SimulatedAnnealing	(	const Real	lambda,
		const Real	T0,
		const Size	K,
		const Real	alpha,
		const RNG &	rng = RNG() )

budget a total of K moves, set temperature T to the initial temperature times \( ( 1 - k/K )^\alpha \) with k being the total number of moves so far. After K moves the temperature is guaranteed to be zero, after that the optimization runs like a deterministic simplex algorithm.

Member Function Documentation

minimize()

template<class RNG>

EndCriteria::Type minimize ( Problem & P, const EndCriteria & endCriteria )

overridevirtual

minimize the optimization problem P

Implements OptimizationMethod.