Catalano.Evolutionary.Metaheuristics.Monoobjective

Class GreyWolfOptimizer

java.lang.Object

Catalano.Evolutionary.Metaheuristics.Monoobjective.BaseEvolutionaryOptimization

Catalano.Evolutionary.Metaheuristics.Monoobjective.GreyWolfOptimizer

public class GreyWolfOptimizer
extends BaseEvolutionaryOptimization

Grey Wolf Optimization (GWO). The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. References: Mirjalili, Seyedali, Seyed Mohammad Mirjalili, and Andrew Lewis. "Grey wolf optimizer." Advances in Engineering Software 69 (2014): 46-61.

Constructor Summary

Constructors

Constructor and Description
GreyWolfOptimizer() Initializes a new instance of the GreyWolfOptimizer class.
GreyWolfOptimizer(int population, int generations) Initializes a new instance of the GreyWolfOptimizer class.

Method Summary

Modifier and Type	Method and Description
void	Compute(IObjectiveFunction function, java.util.List<DoubleRange> boundConstraint) Compute the algorithm.

Methods inherited from class Catalano.Evolutionary.Metaheuristics.Monoobjective.BaseEvolutionaryOptimization

getBest, getError, getGenerations, getNumberOfEvaluations, getPopulationSize, getTolerance, setGenerations, setOnIteratorListener, setPopulationSize, setTolerance

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

GreyWolfOptimizer

public GreyWolfOptimizer()

Initializes a new instance of the GreyWolfOptimizer class.

GreyWolfOptimizer

public GreyWolfOptimizer(int population,
                         int generations)

Initializes a new instance of the GreyWolfOptimizer class.

Parameters:

population - Number of population.

generations - Number of generations.

Method Detail

Compute

public void Compute(IObjectiveFunction function,
                    java.util.List<DoubleRange> boundConstraint)

Description copied from class: BaseEvolutionaryOptimization

Compute the algorithm.

Specified by:

Compute in class BaseEvolutionaryOptimization

Parameters:

function - Function.

boundConstraint - Bounds constraints.