Optimization VIs

Use the Optimization VIs located on the Functions»Analyze»Mathematics»Optimization palette to determine local minima and maxima of real 1D or n-dimension functions. You can choose between optimization algorithms based on derivatives of the function and algorithms working without these derivatives. You also can use special methods like Linear Programming, Levenberg-Marquardt in symbolic form, Pade, and Chebyshev Approximation.

Click the icons for VI descriptions.

Brent with Derivatives 1D Chebyshev Approximation Downhill Simplex nD Conjugate Gradient nD Find All Minima 1D Find All Minima nD Fitting on a Sphere Golden Section 1D Linear Programming Simplex Method Pade Approximation

Brent with Derivatives 1D Find All Minima nD
Chebyshev Approximation Fitting on a Sphere
Conjugate Gradient nD Golden Section 1D
Downhill Simplex nD Linear Programming Simplex Method
Find All Minima 1D Pade Approximation

An overview of the optimization routines is shown in the illustration below.