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Member of the optimization class.

Syntax

xmin = quadprog(q, c, aineq, bineq)

xmin = quadprog(q, c, aineq, bineq, aeq, beq)

xmin = quadprog(q, c, aineq, bineq, aeq, beq, min, max)

[xmin, fval] = quadprog(q, c, aineq, bineq)

[xmin, fval] = quadprog(q, c, aineq, bineq, aeq, beq)

[xmin, fval] = quadprog(q, c, aineq, bineq, aeq, beq, min, max)

[xmin, fval, lambda] = quadprog(q, c, aineq, bineq)

[xmin, fval, lambda] = quadprog(q, c, aineq, bineq, aeq, beq)

[xmin, fval, lambda] = quadprog(q, c, aineq, bineq, aeq, beq, min, max)

Description

Computes the minimum of a quadratic function defined by the following expression: 0.5*x'*q*x+c'*x. LabVIEW constrains the computation based on the inputs that you specify.

Examples

Inputs

Name	Description
q	Specifies a matrix that is part of the quadratic function whose minimum you want to compute. q is a real, double-precision matrix.
c	Specifies a vector that is part of the quadratic function whose minimum you want to compute. c is a real, double-precision vector.
aineq	Specifies a matrix for the linear inequality constraints according to the following equation: aineq*xmin <= bineq. aineq can be []. aineq is a real, double-precision matrix.
bineq	Specifies a vector for the linear inequality constraints according to the following equation: aineq*xmin <= bineq. bineq must be [] when aineq is []. bineq is a real, double-precision vector.
aeq	Specifies a matrix for the linear equality constraints according to the following equation: aeq*xmin = beq. aeq can be []. aeq is a real, double-precision matrix.
beq	Specifies a vector for the linear equality constraints according to the following equation: aeq*xmin = beq. beq must be [] when aeq is []. beq is a real, double-precision vector.
min	Specifies the lower bound for the solution vector according to the following equation: min <= x <= max. min can be []. min is a real, double-precision vector.
max	Specifies the upper bound for the solution vector according to the following equation: min <= x <= max. max can be []. max is a real, double-precision vector.

Outputs

Name	Description
xmin	Returns the point at which the quadratic function has the minimum value. xmin is a real, double-precision vector.
fval	Returns the value of the quadratic function evaluated at xmin. fval is a real, double-precision scalar.
lambda	Returns the lambda values for the solution vector. lambda is a real, double-precision vector.

Examples

Q = [1, 1; 1, 2];
C = [-2; -6];
AINEQ = [0.5, 0.5; -1, 2];
BINEQ = [1, 2];
MIN = [0; 0];
XMIN = quadprog(Q, C, AINEQ, BINEQ, [], [], MIN);

Related Topics

linprog