C# 클래스 SwarmOps.Optimizers.DE

Differential Evolution (DE) optimizer originally due to Storner and Price (1). This simple and efficient variant is based on the The Joker variant by Pedersen et al. (2). It has been found to be very versatile and works well on a wide range of optimization problems, but may require tuning (or meta-optimization) of its parameters.

References: (1) R. Storn and K. Price. Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization, 11:341-359, 1997. (2) M.E.H. Pedersen and A.J. Chipperfield. Parameter tuning versus adaptation: proof of principle study on differential evolution. Technical Report HL0802, Hvass Laboratories, 2008

상속: Optimizer

파일 보기 프로젝트 열기: DanWBR/dwsim3

공개 메소드들

메소드	설명
DE ( ) : System.Diagnostics	Construct the object.
DE ( Problem problem ) : System.Diagnostics	Construct the object.
GetCR ( double parameters ) : double	Get parameter, CR, aka. crossover probability.
GetF ( double parameters ) : double	Get parameter, F, aka. differential weight.
GetNumAgents ( double parameters ) : int	Get parameter, Number of agents, aka. population size.
Optimize ( double parameters ) : Result	Perform one optimization run and return the best found solution.

메소드 상세

DE() 공개 메소드

Construct the object.

public DE ( ) : System.Diagnostics
리턴	System.Diagnostics

DE() 공개 메소드

Construct the object.

public DE ( Problem problem ) : System.Diagnostics
problem	Problem	Problem to optimize.
리턴	System.Diagnostics

GetCR() 공개 메소드

Get parameter, CR, aka. crossover probability.

public GetCR ( double parameters ) : double
parameters	double	Optimizer parameters.
리턴	double

GetF() 공개 메소드

Get parameter, F, aka. differential weight.

public GetF ( double parameters ) : double
parameters	double	Optimizer parameters.
리턴	double

GetNumAgents() 공개 메소드

Get parameter, Number of agents, aka. population size.

public GetNumAgents ( double parameters ) : int
parameters	double	Optimizer parameters.
리턴	int

Optimize() 공개 메소드

Perform one optimization run and return the best found solution.

public Optimize ( double parameters ) : Result
parameters	double	Control parameters for the optimizer.
리턴	Result