FIGA< S > Class Template Reference
Class to represents a First Improve Genetic Algorithm (FIGA). This algorithms differentiate from others because of using a first improves replacement method. Each new individual replaces its parent if the fitness has improved. More...
#include <FIGA.h>
Inheritance diagram for FIGA< S >:
Public Member Functions | |
| FIGA () | |
| Creates a RAW FIGA instance. More... | |
| string | getName () const override |
| Get the Name. More... | |
| string | getID () const override |
| Get the ID of the algorithm. More... | |
 Public Member Functions inherited from AbstractGA< S > | |
| AbstractGA () | |
| Creates a new AbstractGA which initialises all parameter to default. The operators will be set to null. More... | |
| json | to_json () const override |
| Creates and returns JSON object with the GA information. More... | |
| virtual Front< S > | getResults () const |
| Returns a front with the feasible non repeated individuals in the last population of the Genetic Algorithm. This is the final solution of the algorithm to the problem at hand. More... | |
| void | run () override |
| Runs the evolutionary process. This is the main EA method. This methods is in charge of: More... | |
| void | setProblem (shared_ptr< Problem< S >> prob) override |
| Uptades the problem to solve using a share_ptr. The problem must be single-objective. More... | |
| void | setProblem (Problem< S > *prob) override |
| Uptades the problem to solve using a raw pointer. The problem must be single-objective. More... | |
| double | getMutationRate () const |
| Gets the mutation rate. More... | |
| void | setMutationRate (double mutationRate) |
| Updates the mutation rate. More... | |
| double | getCrossRate () const |
| Gets the crossover rate. More... | |
| void | setCrossRate (double crossRate) |
| Updates the crossover rate. More... | |
| const Mutation< S > * | getMutation () const |
| Gets a pointer to the mutation operator. More... | |
| void | setMutation (unique_ptr< Mutation< S >> mutation) |
| Updates the mutation operator. Takes a unique_ptr pointing to the new Mutation operator and takes the ownership. More... | |
| const Crossover< S > * | getCrossover () const |
| Returns a raw pointer to the crossover operator. More... | |
| void | setCrossover (unique_ptr< Crossover< S >> crossover) |
| Updates the crossover operator. Takes a unique_ptr pointing to the new Crossover operator and takes the ownership. More... | |
| const Selection< S > * | getSelection () const |
| Returns a raw pointer of the selection operator. More... | |
| void | setSelection (unique_ptr< Selection< S >> selectionOperator) |
| Updates the selection operator. Takes a unique_ptr pointing to the new Selection operator and takes the ownership. 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... | |
| 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 | |
| void | updateProgress () override |
| Updates the performed evaluations to the population size on each call. More... | |
| Protected Member Functions inherited from AbstractGA< S > | |
| virtual void | initProgress () |
| Starts the evolutionary process. By default this methods sets the number of performed evaluations to the population size since it considers that all individuals have been evaluated in the createInitialPopulation method. More... | |
| virtual void | finishProgress () |
| Finishes the evolutionary process by computing the elapsed time. More... | |
| virtual bool | isStoppingConditionReached () |
| Checks whether the evolutionary process has reached the maximum limit. More... | |
| virtual void | createInitialPopulation () |
| Creates the initial population of individuals before starting the evolutionary process. More... | |
| virtual void | evaluatePopulation (vector< S > &pop) |
| Evaluates the entire population of individuals using the problem evaluation function. More... | |
| virtual vector< S > | createMating () |
| Generates the mating population of individuals to be evaluated. The individuals are selected and after that the genetic operators are applied here. More... | |
| virtual void | reproduction (S &, S &) |
| Applies the genetic operator. This methods is invoked from createMating. More... | |
| Protected Member Functions inherited from AbstractEA< S > | |
| virtual void | updateEvolution (vector< S > &pop) |
| virtual void | updateEvolution (const int &checkpoint, vector< S > &) |
Additional Inherited Members | |
| Static Public Attributes inherited from AbstractGA< S > | |
| static double | DEFAULT_MUTATION_RATE = 0.05 |
| Default mutation rate for GAs set to 0.05. More... | |
| static double | DEFAULT_CROSSOVER_RATE = 0.8 |
| Default crossover rate to GAs set to 0.8. More... | |
| static int | DEFAULT_POPULATION_SIZE = 32 |
| Default population size to GAs set to 32 individuals. More... | |
| 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 AbstractGA< S > | |
| double | mutationRate |
| double | crossRate |
| unique_ptr< Mutation< S > > | mutation |
| unique_ptr< Crossover< S > > | crossover |
| unique_ptr< Selection< S > > | selection |
| unique_ptr< Replacement< S > > | replacement |
| 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 FIGA< S >
Class to represents a First Improve Genetic Algorithm (FIGA). This algorithms differentiate from others because of using a first improves replacement method. Each new individual replaces its parent if the fitness has improved.
- Template Parameters
-
S Type of individual in the population
Constructor & Destructor Documentation
◆ FIGA()
Member Function Documentation
◆ getID()
template<class S >
|
inlineoverridevirtual |
◆ getName()
template<class S >
|
inlineoverridevirtual |
◆ updateProgress()
template<class S >
|
overrideprotectedvirtual |
Updates the performed evaluations to the population size on each call.
- Template Parameters
-
Problem S
Implements AbstractGA< S >.
The documentation for this class was generated from the following file:
- include/dignea/algorithms/singleobjective/FIGA.h
