Quadratic programming is a problem of optimizing a quadratic function of several variables subject to linear constraints on these variables.
A quadratic programming problem aims at finding minimum of a quadratic function:
Under the constraints:
Where:
f(x). Function of n-variables.
x. n-vector of the variables.
c. n-vector of linear component in the criterion function.
H. n x n is symmetric matrix of quadratic component of the criterion function.
A. m x n - matrix of linear constraints, where m is a number of linear constraints.
l0, u0. n - vectors of limits determining direct constraints.
l, u. m - vectors of limits determining linear constraints.
NOTE. To solve quadratic programming task, you should execute integration with LPSolve.
See also:
Library of Methods and Models | ISmQuadraticProgramming