Base heuristic class. This is the skeleton for future heuristic implementations. Extends AbstractEA for compatibility with EIG. More...

#include <Heuristic.h>

Inheritance diagram for Heuristic< S >:

Public Member Functions
virtual void	run ()=0
	Main method of the EA. Runs the algorithm but must be implemented in the subclasses.

virtual string	getName () const =0
	Returns the name of the algorithm, this is used in the to_json method. Must be implemented in the subclasses. More...

virtual string	getID () const =0
	Returns the identificator of the algorithm, this is used in the to_json method. Must be implemented in the subclasses. It should return the acronym of useful id for a particular configuration. More...

virtual json	to_json () const
	Returns the JSON representation of the Heuristic. More...

virtual Front< S >	getResults () const =0
	Returns a Front object with all the solutions of the evolutionary process. This method must be implemented in the subclasses. More...

Public Member Functions inherited from AbstractEA< S >
	AbstractEA ()
	Construct a new Abstract EA object with default parameter values. More...

	AbstractEA (const int &maxEvals, const int &popsize)
	AbstractEA constructor which initialises the parameters maxEvalautions and populationSize. More...

	AbstractEA (unique_ptr< PopulationEvaluator< S >>, const int &maxEvals, const int &popsize)
	AbstractEA constructor which initialises the parameters maxEvalautions, the populationSize and the evaluator approach. More...

int	getPopulationSize () const
	Get the population size. More...

void	setPopulationSize (int pSize)
	Setter to update the population size. More...

double	getElapsedTime () const
	Get the elapsed time of the evolutionary process. More...

const vector< S > &	getPopulation () const
	Gets a reference of the population. More...

int	getMaxEvaluations () const
	Get the maximum number of evaluations to perform. More...

void	setMaxEvaluations (int maxEval)
	Set a new maximum number of evaluations to perform. More...

const Problem< S > *	getProblem () const
	Gets a pointer to the problem which is being solved. More...

virtual void	setProblem (shared_ptr< Problem< S >> prob)
	Set the new problem to solve. Uses a shared_ptr pointer which updates the reference counter. Does no take the ownership. More...

virtual void	setProblem (Problem< S > *prob)
	Set the new problem to solve. Uses a raw pointer and takes the ownership of the object. More...

PopulationEvaluator< S > *	getEvaluator () const
	Gets a pointer to the population evaluator system. More...

void	setEvaluator (unique_ptr< PopulationEvaluator< S >> eval)
	Updates the population evaluator system with the unique_ptr. The method takes the ownership of the object behind. More...

int	getPerformedEvaluations () const
	Get the performed evaluations. More...

void	setPerformedEvaluations (int pEvals)
	Set the Performed Evaluations. Useful for the updateProgress method. More...

void	setPopulation (const vector< S > &pop)
	Set the Population. More...

virtual Evolution< S >	getEvolution () const
	Get the Evolution data. More...

int	getPrintingInterval () const
	Get the interval of checkpoints. More...

Protected Member Functions
virtual void	initProgress ()
	Not implemented. Nothing really to do here.

virtual void	updateProgress ()
	Not implemented. Nothing really to do here.

void	finishProgress () override
	Finishes the progress of the Heuristic by computing the elapsed time. More...

bool	isStoppingConditionReached () override
	Always returns false. TODO: Refactor to inherit from Algorithm. More...

virtual void	createInitialPopulation ()
	Not implemented. Nothing really to do here.

virtual void	evaluatePopulation (vector< S > &)
	Not implemented. Nothing really to do here.

virtual void	updateEvolution (vector< S > &)
	Not implemented. Nothing really to do here.

virtual void	updateEvolution (const int &checkpoint, vector< S > &)
	Not implemented. Nothing really to do here.

Additional Inherited Members
Static Public Attributes inherited from AbstractEA< S >
static const int	DEFAULT_POPULATION_SIZE = 100
	Default population size equal to 100 individuals. More...

static const int	DEFAULT_EVALUATIONS_LIMIT = 100000
	Default evaluation limit equal to 100000 evaluations. More...

static const std::string	NAME = "Algorithm"

static const std::string	MAX_EVALUATIONS = "Max Evaluations"

static const std::string	POP_SIZE = "Population Size"

static const std::string	ELAPSED_TIME = "Elapsed Time"

static const std::string	EVALUATOR = "Evaluator"

static const int	EVOLUTION_SIZE = 10

Protected Attributes inherited from AbstractEA< S >
int	maxEvaluations

int	performedEvaluations

int	populationSize

vector< S >	population

shared_ptr< Problem< S > >	problem

unique_ptr< PopulationEvaluator< S > >	evaluator

Evolution< S >	evolution

AvgEvolution< S >	avgEvolution

std::chrono::system_clock::time_point	startTime

std::chrono::system_clock::time_point	endTime

double	elapsedTime

int	nextCheckpoint

int	evolutionInterval

Detailed Description

template<class S>
class Heuristic< S >

Base heuristic class. This is the skeleton for future heuristic implementations. Extends AbstractEA for compatibility with EIG.

Template Parameters

S	Type of the solutions

Member Function Documentation

◆ finishProgress()

template<class S >

void Heuristic< S >::finishProgress

overrideprotectedvirtual

Finishes the progress of the Heuristic by computing the elapsed time.

Template Parameters

S

Implements AbstractEA< S >.

◆ getID()

template<class S >

virtual string Heuristic< S >::getID ( ) const

pure virtual

Returns the identificator of the algorithm, this is used in the to_json method. Must be implemented in the subclasses. It should return the acronym of useful id for a particular configuration.

Returns: string

Implements AbstractEA< S >.

Implemented in tsp_heuristics::TwoOpt, tsp_heuristics::NearestNeighbour, tsp_heuristics::Greedy, MPW, MiW, MinKnap, MaP, ExpKnap, Default, Combo, WorstFit, NextFit, FirstFit, and BestFit.

◆ getName()

template<class S >

virtual string Heuristic< S >::getName ( ) const

pure virtual

Returns the name of the algorithm, this is used in the to_json method. Must be implemented in the subclasses.

Returns: string

Implements AbstractEA< S >.

Implemented in tsp_heuristics::TwoOpt, tsp_heuristics::NearestNeighbour, tsp_heuristics::Greedy, MPW, MiW, MinKnap, MaP, ExpKnap, Default, Combo, WorstFit, NextFit, FirstFit, and BestFit.

◆ getResults()

template<class S >

virtual Front<S> Heuristic< S >::getResults ( ) const

pure virtual

Returns a Front object with all the solutions of the evolutionary process. This method must be implemented in the subclasses.

Returns: Front

Implements AbstractEA< S >.

Implemented in tsp_heuristics::TwoOpt, tsp_heuristics::NearestNeighbour, tsp_heuristics::Greedy, MinKnap, ExpKnap, Default, Combo, WorstFit, NextFit, FirstFit, and BestFit.

◆ isStoppingConditionReached()

template<class S >

bool Heuristic< S >::isStoppingConditionReached ( )

inlineoverrideprotectedvirtual

Always returns false. TODO: Refactor to inherit from Algorithm.

Returns: false

Implements AbstractEA< S >.

◆ to_json()

template<class S >

json Heuristic< S >::to_json

virtual

Returns the JSON representation of the Heuristic.

Template Parameters

S

Returns: json

Reimplemented from AbstractEA< S >.

The documentation for this class was generated from the following file:

include/dignea/core/Heuristic.h

Public Member Functions

Protected Member Functions

Additional Inherited Members

Detailed Description

template<class S> class Heuristic< S >

Member Function Documentation

◆ finishProgress()

◆ getID()

◆ getName()

◆ getResults()

◆ isStoppingConditionReached()

◆ to_json()

template<class S>
class Heuristic< S >