Dew MtxVec NET
Optimization Unit
Summary
Function minimization routines.
Description
Introduces the following algorithms for finding the minimum of scalar function of several variables:

Introduces the following algorithms for finding the minimum of vector function of several variables:
Introduces the following algorithms for finding the minimum of function of single variable:

In addition, several routines for linear programming (LP) are also provided. The following algorithms are supported:

Types

 Name  Summary 
TEPSArray Stores the stopping tests for TR optimization. 
TGrad Defines the procedure for calculating the gradient of a real function. 
TGradHess Defines the procedure for calculating the gradient and Hessian matrix of a real function. 
TJacobianFunction Defines procedure for calculating the jacobian matrix. 
TLPAlgorithm Linear programming algorithm. 
TLPSolution LP system solution. 
TOptMethod Optimization methods. 
TOptStopReason Why the main loop in optimization stopped. 
TVectorFunction Defines vector function of several variables. 

Routines

 Name  Summary 
BFGS Minimizes the function of several variables by using the Quasi-Newton optimization algorithm. 
ConjGrad Minimizes the function of several variables by using the Conjugate gradient optimization algorithm. 
CPA Gomory's cutting plane algorithm for solving the integer programming problem. 
Marquardt Minimizes the function of several variables by using the Marquardt optimization algorithm. 
MinBrent Minimizes single variable function. 
Simplex Minimizes the function of several variables by using the Nelder-Mead (Simplex) optimization method. 
SimplexDual Linear optimization by Dual Simplex algorithm. 
SimplexLP Linear optimization by using Simplex method. 
SimplexTwoPhase Linear optimization by Two-Phase Simplex algorithm. 
TrustRegion Trust region algorithm for finding minimum of vector function. 

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