com.cureos.numerics

Class Cobyla

java.lang.Object

com.cureos.numerics.Cobyla

public class Cobyla
extends java.lang.Object

Constrained Optimization BY Linear Approximation in Java. COBYLA2 is an implementation of Powell’s nonlinear derivative-free constrained optimization that uses a linear approximation approach. The algorithm is a sequential trust-region algorithm that employs linear approximations to the objective and constraint functions, where the approximations are formed by linear interpolation at n+1 points in the space of the variables and tries to maintain a regular-shaped simplex over iterations. It solves nonsmooth NLP with a moderate number of variables (about 100). Inequality constraints only. The initial point X is taken as one vertex of the initial simplex with zero being another, so, X should not be entered as the zero vector.

Constructor Summary

Constructors

Constructor and Description
Cobyla() Initialize calculations.

Method Summary

Modifier and Type	Method and Description
static CobylaExitStatus	FindMinimum(Calcfc calcfc, int n, int m, double[] xin, double rhobeg, double rhoend, int iprint, int maxfun) Minimizes the objective function F with respect to a set of inequality constraints CON, and returns the optimal variable array.
double[]	getOutput() Return output of minimization.

Methods inherited from class java.lang.Object

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

Constructor Detail

Cobyla

public Cobyla()

Initialize calculations.

Method Detail

FindMinimum

public static CobylaExitStatus FindMinimum(Calcfc calcfc,
                                           int n,
                                           int m,
                                           double[] xin,
                                           double rhobeg,
                                           double rhoend,
                                           int iprint,
                                           int maxfun)

Minimizes the objective function F with respect to a set of inequality constraints CON, and returns the optimal variable array. F and CON may be non-linear, and should preferably be smooth.

Parameters:

calcfc - Interface implementation for calculating objective function and constraints.

n - Number of variables.

m - Number of constraints.

xin - On input initial values of the variables (zero-based array). On output optimal values of the variables obtained in the COBYLA minimization.

rhobeg - Initial size of the simplex.

rhoend - Final value of the simplex.

iprint - Print level, 0 <= iprint <= 3, where 0 provides no output and 3 provides full output to the console.

maxfun - Maximum number of function evaluations before terminating.

Returns:

Exit status of the COBYLA2 optimization.

getOutput

public double[] getOutput()

Return output of minimization.

Returns:

x Ouput of minimization