randomQP: randomQP

In QPmin: Linearly Constrained Indefinite Quadratic Program Solver

Description

Generates a non-separable random quadratic program of the specified type.

Usage

randomQP(n, type = c("convex", "concave", "indefinite"))

Arguments

n	The random problem generated will have n variables and m = 3n/2 constraints. Must be an even number.
type	Specifies the curvature of the objective function.

Details

The algorithm is based on Calamai, Vicente, and Judice (1993). It generates a random quadratic program with the following form

\min_x \frac{1}{2} x^T G x + x^T g

Ax ≥q b

Value

G	The quadratic component of the objective function. Must be symmetric.
g	The linear component of the objective function
A	The constraints coefficient matrix. This matrix has $n$ rows and $m$ columns.
b	The vector with the lower bounds on the constraints.
opt	An approximate expected value at the optimum solutions.
solutions	A list containing all of the global solutions to the problem.

Author(s)

Andrea Giusto

References

“A new technique for generating quadratic programming test problems,” Calamai P.H., L.N. Vicente, and J.J. Judice, Mathematical Programming 61 (1993), pp. 215-231.

Examples

n <- 8

RP <- randomQP(n, "concave")

RP2 <- randomQP(n, "indefinite")

RP3 <- randomQP(n, "convex")

QPmin documentation built on April 15, 2021, 5:06 p.m.