Package org.moeaframework.algorithm.single

Class RepeatedSingleObjective

java.lang.Object

org.moeaframework.algorithm.AbstractAlgorithm

org.moeaframework.algorithm.single.RepeatedSingleObjective

All Implemented Interfaces:

Algorithm, Stateful

public class RepeatedSingleObjective
extends AbstractAlgorithm

Instantiates and runs several instances of a single objective algorithm. This is intended to be used with single-objective optimizers that use weighted aggregation of the objectives. This is based on the Repeated Single Objective (RSO) algorithm by E. J. Hughes [1], where they investigate running many single-objective optimizers (one many) compared to running a single many-objective optimizer (many once).

Be mindful of how running multiple instances affects the AbstractAlgorithm.step(). Each step performs one iteration of each instance. Thus, given 50 instances of an algorithm with a population size of 100, then 5000 evaluations will occur each step. In [1], they decrease the population size for the single objective optimizers.

References:

1. E. J. Hughes. "Evolutionary many-objective optimization: many once or one many." 2005 IEEE Congress on Evolutionary Computation, pp. 222-227.

Field Summary

Fields inherited from class org.moeaframework.algorithm.AbstractAlgorithm

initialized, numberOfEvaluations, problem, terminated

Constructor Summary

Constructors

Constructor	Description
RepeatedSingleObjective(Problem problem, int instances, String algorithmName, TypedProperties properties)	Constructs a new instance of the RSO algorithm using the given single-objective algorithm.
RepeatedSingleObjective(Problem problem, int instances, BiFunction<Problem,double[],Algorithm> creator)	Constructs a new instance of the RSO algorithm using randomly-generated weights.
RepeatedSingleObjective(Problem problem, WeightGenerator weightGenerator, BiFunction<Problem,double[],Algorithm> creator)	Constructs a new instance of the RSO algorithm.

Method Summary

Modifier and Type	Method	Description
int	getNumberOfEvaluations()	Returns the number of times the evaluate method was invoked.
NondominatedPopulation	getResult()	Returns the current best-known result.
protected void	initialize()	Performs any initialization that is required by this algorithm.
protected void	iterate()	Performs one iteration of the algorithm.
void	loadState(ObjectInputStream stream)	Loads the state of this object from the stream.
void	saveState(ObjectOutputStream stream)	Writes the state of this object to the stream.

Methods inherited from class org.moeaframework.algorithm.AbstractAlgorithm

assertNotInitialized, evaluate, evaluateAll, evaluateAll, getProblem, isInitialized, isTerminated, step, terminate

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.moeaframework.core.Algorithm

run, run

Constructor Details

RepeatedSingleObjective

public RepeatedSingleObjective(Problem problem,
 int instances,
 String algorithmName,
 TypedProperties properties)

Constructs a new instance of the RSO algorithm using the given single-objective algorithm. The properties are passed to each individual algorithm with the addition of a "weights" parameter, which is randomly-generated for each instance.

Parameters:

problem - the problem to solve

algorithmName - the algorithm name

properties - the algorithm properties

instances - the number of instances

RepeatedSingleObjective

public RepeatedSingleObjective(Problem problem,
 int instances,
 BiFunction<Problem,double[],Algorithm> creator)

Constructs a new instance of the RSO algorithm using randomly-generated weights.

Parameters:

problem - the problem to solve

instances - the number of single-objective algorithm instances to create using random weights

creator - function that creates a single-objective algorithm for the given weight vector

RepeatedSingleObjective

public RepeatedSingleObjective(Problem problem,
 WeightGenerator weightGenerator,
 BiFunction<Problem,double[],Algorithm> creator)

Constructs a new instance of the RSO algorithm. The weight generator defines the number of instances.

Parameters:

problem - the problem to solve

weightGenerator - generates the weight vectors used to configure each single-objective algorithm

creator - function that creates a single-objective algorithm for the given weight vector

Method Details

getNumberOfEvaluations

public int getNumberOfEvaluations()

Description copied from interface: Algorithm

Returns the number of times the evaluate method was invoked. This is the primary measure of runtime for optimization algorithms.

Specified by:

getNumberOfEvaluations in interface Algorithm

Overrides:

getNumberOfEvaluations in class AbstractAlgorithm

Returns:

the number of times the evaluate method was invoked

getResult

public NondominatedPopulation getResult()

Description copied from interface: Algorithm

Returns the current best-known result.

Returns:

the current best-known result

initialize

protected void initialize()

Description copied from class: AbstractAlgorithm

Performs any initialization that is required by this algorithm. This method is called automatically on the first invocation of AbstractAlgorithm.step(). Implementations should always invoke super.initialize() to ensure the algorithm is initialized correctly.

Overrides:

initialize in class AbstractAlgorithm

iterate

protected void iterate()

Description copied from class: AbstractAlgorithm

Performs one iteration of the algorithm. This method should be overridden by implementations to perform each logical iteration of the algorithm.

Specified by:

iterate in class AbstractAlgorithm

saveState

public void saveState(ObjectOutputStream stream)
               throws IOException

Description copied from interface: Stateful

Writes the state of this object to the stream. The order that objects are written to the stream is important. We recommend first calling super.saveState(stream) followed by writing each field.

Specified by:

saveState in interface Stateful

Overrides:

saveState in class AbstractAlgorithm

Parameters:

stream - the stream

Throws:

IOException - if an I/O error occurred

loadState

public void loadState(ObjectInputStream stream)
               throws IOException,
ClassNotFoundException

Description copied from interface: Stateful

Loads the state of this object from the stream. The order for reading objects from the stream must match the order they are written to the stream in Stateful.saveState(ObjectOutputStream).

Specified by:

loadState in interface Stateful

Overrides:

loadState in class AbstractAlgorithm

Parameters:

stream - the stream

Throws:

IOException - if an I/O error occurred

ClassNotFoundException - if the stream referenced a class that is not defined