C# 클래스 SwarmOps.Optimizers.MetaFitness

Compute the standard Meta-Fitness measure, that is, perform a number of optimization runs on different problems and sum their results.

Preemptive Fitness Evaluation is used in that optimizations will be attempted aborted once the meta-fitness becomes worse than the Preemptive Fitness Limit (aka. fitnessLimit). In addition, the array of problems are being sorted at the end of each meta-fitness computation, so as to allow the worst performing problems to be optimized first in the next meta-fitness computation, so as to decrease the computation time further still.

상속: Problem

파일 보기 프로젝트 열기: DanWBR/dwsim3

보호된 프로퍼티들

프로퍼티	타입	설명
ProblemIndex	ProblemIndex

공개 메소드들

메소드	설명
BeginOptimizationRun ( ) : void	At beginning of new meta-optimization run print a newline.
EnforceConstraints ( double &parameters ) : bool	Enforce constraints and evaluate feasiblity.
Feasible ( double parameters ) : bool	Evaluate feasibility (constraint satisfaction).
Fitness ( double parameters, double fitnessLimit ) : double	Compute the meta-fitness measure by passing the given parameters to the Optimizer, and perform optimization runs on the array of problems until the fitness compute exceeds the fitnessLimit.
MetaFitness ( Optimizer optimizer, Problem problems, int numRuns, int maxIterations ) : System.Diagnostics	Construct the object, un-weighted problems.
MetaFitness ( Optimizer optimizer, WeightedProblem weightedProblems, int numRuns, int maxIterations ) : System.Diagnostics	Construct the object, weighted problems.

메소드 상세

BeginOptimizationRun() 공개 메소드

At beginning of new meta-optimization run print a newline.

public BeginOptimizationRun ( ) : void
리턴	void

EnforceConstraints() 공개 메소드

Enforce constraints and evaluate feasiblity.

public EnforceConstraints ( double &parameters ) : bool
parameters	double	Parameters to use for the Optimizer.
리턴	bool

Feasible() 공개 메소드

Evaluate feasibility (constraint satisfaction).

public Feasible ( double parameters ) : bool
parameters	double	Parameters to use for the Optimizer.
리턴	bool

Fitness() 공개 메소드

Compute the meta-fitness measure by passing the given parameters to the Optimizer, and perform optimization runs on the array of problems until the fitness compute exceeds the fitnessLimit.

public Fitness ( double parameters, double fitnessLimit ) : double
parameters	double	Parameters to use for the Optimizer.
fitnessLimit	double	Preemptive Fitness Limit
리턴	double

MetaFitness() 공개 메소드

Construct the object, un-weighted problems.

public MetaFitness ( Optimizer optimizer, Problem problems, int numRuns, int maxIterations ) : System.Diagnostics
optimizer	Optimizer	Optimizer to be used.
problems	Problem	Array of problems to be optimized.
numRuns	int	Number of optimization runs per problem.
maxIterations	int	Max number of optimization iterations.
리턴	System.Diagnostics

MetaFitness() 공개 메소드

Construct the object, weighted problems.

public MetaFitness ( Optimizer optimizer, WeightedProblem weightedProblems, int numRuns, int maxIterations ) : System.Diagnostics
optimizer	Optimizer	Optimize to be used.
weightedProblems	WeightedProblem	Array of weighted problems to be optimized.
numRuns	int	Number of optimization runs per problem.
maxIterations	int	Max number of optimization iterations.
리턴	System.Diagnostics

프로퍼티 상세

ProblemIndex 보호되어 있는 프로퍼티

Sorted index of optimization problems.

protected ProblemIndex ProblemIndex
리턴	ProblemIndex