Mathematical Linear Programming.
rsolveLP(objective, lower=0, upper=1, linCons,
control=list(solver="glpk", invoke=c("R", "AMPL", "NEOS")))rglpkLP(objective, lower=0, upper=1, linCons, control=list())
glpkLP
glpkLPControl(solver = "glpk", project="r", trace=FALSE)
rsymphonyLP(objective, lower=0, upper=1, linCons, control=list())
symphonyLP
symphonyLPControl(solver="symphony", project="r", trace=FALSE)
ramplLP(objective, lower = 0, upper = 1, linCons, control=list())
amplLP(objective, x_L=NULL, x_U=NULL, A=NULL, b_L=NULL, b_U=NULL,
control=list())
amplLPControl(solver="ipopt", project="ampl", inf=1e12, trace=FALSE)
rneosLP(objective, lower = 0, upper = 1, linCons, control=list())
neosLP(objective, x_L=NULL, x_U=NULL, A=NULL, b_L=NULL, b_U=NULL,
control=list())
neosLPControl(solver="ipopt", category="lp", project="neos",
inf=1e12, trace=FALSE)
a list of class solver
with the following named ebtries:
opt
,
solution
,
objective
,
status
,
message
,
solver
,
version
.
a numeric vector.
lower and upper bounds.
list of linear constraints: mat, lower, upper.
control list.
lower and upper box bounds.
linear constraints matrix.
lower and upper linear constraints bounds.
a character string, the solver name.
a character string, the NEOS category name.
a character string, the AMPL project name.
a numeric value, the maximum value used for bounds.
a logical flag, if TRUE the optimization will be traced.
Wuertz, D., Chalabi, Y., Chen W., Ellis A. (2009); Portfolio Optimization with R/Rmetrics, Rmetrics eBook, Rmetrics Association and Finance Online, Zurich.