cop {optiSolve}

Constrained Optimization Problem

Description

Define a constrained optimization problem with a linear, quadratic, or rational objective function, and linear, quadratic, rational, and boundary constraints.

Usage

cop(f, max=FALSE, lb=NULL, ub=NULL, lc=NULL, ...)

Arguments

f

Objective function, defined with function linfun, quadfun, or ratiofun.

max

Logical value. Should the function be maximized? This is possible only for linear objective functions.

lb

Lower bounds for the variables, defined with function lbcon.

ub

Upper bounds for the variables, defined with function ubcon.

lc

Linear inequality and equality constraints, defined with function lincon.

...

Quadratic and rational inequality constraints, defined with functions quadcon and ratiocon.

Details

Define a constrained optimization problem with a linear, quadratic, or rational objective function, and linear, quadratic, rational, and boundary constraints. The optimization problem can be solved with function solvecop.

Value

An object of class COP, which may contain the following components

f

List with S3-class "linFun", "quadFun", or "ratioFun", defining the objective function

max

Logical value. Should the objective function be maximized?

lb

List with S3-class "lbCon", defining lower bounds.

ub

List with S3-class "ubCon", defining upper bounds.

lc

List with S3-class "linCon", defining linear constraints

qc

List with S3-class "quadCon", defining quadratic constraints

rc

List with S3-class "ratioCon", defining rational constraints

x

Vector with NAs

id

Vector with names of the variables that are to be optimized

madeDefinite

Logical variable indicating whether non-positive-semidefinite matrices have already been approximated by positive-definite matrices.

Author(s)

Robin Wellmann

See Also

The main function for solving constrained programming problems is solvecop.