gurobi.optim: LP and QP solver by 'Gurobi'

In conroylau/lpinfer: An R Package for Inference in Linear Programs

LP and QP solver by Gurobi

Description

This function computes the solution to the linear or quadratic program using the Gurobi package. This function can have linear and/or quadratic constraints.

Usage

gurobi.optim(
  Af,
  bf,
  nf,
  A,
  rhs,
  sense,
  modelsense,
  lb,
  qc = NULL,
  weight = NULL,
  ...
)

Arguments

Af	The matrix that is involved in the objective function.
bf	The vector that is involved in the objective function.
nf	The number of observations in the data frame.
A	The constraint matrix.
rhs	The rhs vector for the linear constraints.
sense	The sense of the linear constraints.
modelsense	The indicator of whether the model is to max or min an objective function.
lb	The lower bound vector.
qc	The list of quadratic constraint(s). There can be multiple quadratic constraints. Each constraint has to be a list.
weight	The weighting matrix.
...	List of options to be passed to the Gurobi solver. This part is optional.

Value

Returns the optimal point, the optimal value and the status of the solution.

objval	The optimal value.
x	The optimal point.
status	The status of the optimization problem.

conroylau/lpinfer documentation built on Oct. 23, 2022, 9:21 a.m.