llgpcp: Solve an LLGP problem with complementary pivoting

In goalprog: Weighted and lexicographical goal programming and optimization

Description

Solve a lexicographical linear goal programming (LLGP) problem using a modified primal simplex algorithm with complementary pivoting of the decision variables.

Usage

llgpcp(coefficients, targets, achievements, variable.classes, maxiter = 1000, verbose = FALSE)

Arguments

coefficients	A matrix of coefficients for the linear objective functions
targets	A vector of target values for the objective functions
achievements	A data frame with the deviation variables for each objective together with the priority level
variable.classes	A data frame with the complementary class assignments for the decision variables
maxiter	The maximum number of interations with a default value of 1000
verbose	A logical value that determines if intermediate tableaus are to be printed

Details

The function implements the Ignizio (1976) modified simplex algorithm. When the user selects verbose=TRUE, the modified simplex tableau is printed at each iteration.

Value

An object of class 'llgpcp' which is a list with three named components

tab	An object of type 'llgpcptab' for the augmented modified simplex tableau
solution	An object of typel 'llgpout' for the optimal solution
converged	A logical value that determines if the algorithm converged to the optimal solution

Author(s)

Frederick Novomestky [e-mail]

References

Ignizio, J. P. (1976). Goal Programming and Extensions, Lexington Books, D. C. Heath and Company.

See Also

check.tb, check.ev.cp, calc.ti.k, calc.ta.k, ev.llgp, dv.llgp, piv.llgp, llgpcptab, llgpout

goalprog documentation built on May 30, 2017, 5:07 a.m.