DifferentialEvolution Class Reference

Differential Evolution configuration object. More...

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

Inheritance diagram for DifferentialEvolution:

Public Types
enum	Strategy {   Rand1Standard, BestMemberWithJitter, CurrentToBest2Diffs, Rand1DiffWithPerVectorDither,   Rand1DiffWithDither, EitherOrWithOptimalRecombination, Rand1SelfadaptiveWithRotation }
enum	CrossoverType { Normal, Binomial, Exponential }

Public Member Functions
	rng_ (configuration.seed)
virtual EndCriteria::Type	minimize (Problem &p, const EndCriteria &endCriteria)
	minimize the optimization problem P
const Configuration &	configuration () const

Public Attributes
	__pad0__: configuration_(configuration)

Detailed Description

Differential Evolution configuration object.

The algorithm and strategy names are taken from here:

Price, K., Storn, R., 1997. Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces. Journal of Global Optimization, Kluwer Academic Publishers, 1997, Vol. 11, pp. 341 - 359.

There are seven basic strategies for creating mutant population currently implemented. Three basic crossover types are also available.

Future development: 1) base element type to be extracted 2) L differences to be used instead of fixed number 3) various weights distributions for the differences (dither etc.) 4) printFullInfo parameter usage to track the algorithm

Warning:

This was reported to fail tests on Mac OS X 10.8.4.

OptimizationMethod using Differential Evolution algorithm