如何将 Gurobi 的 vbasis 和 cbasis 与 R-Interface 一起使用？

Question

我在文档中找到了解释 here and here:

vbasis
Variable basis status values for the computed optimal basis. You generally should not concern yourself with the contents of this array. If you wish to use an advanced start later, you would simply copy the vbasis and cbasis arrays into the corresponding fields for the next model. This array contains one entry for each column of A.

cbasis
Constraint basis status values for the computed optimal basis. This array contains one entry for each row of A.

稍后：

Finally, if the final solution is a basic solution (computed by simplex), then vbasis and cbasis will be present.

我不明白为什么我没有得到这些值 - 也许我错过了什么。

可重现的例子：

model <- list()
model$A          <- matrix(c(1, 1, 1, 0, 
                             1, 0, 0, 0, 
                             0, 1, 0, 0, 
                             0, 0, 1, 0, 
                             0, 0, 0, 1), nrow = 5, ncol = 4, byrow = T)
model$obj        <- c(2, -5, 3, 10)
model$modelsense <- "min"
model$rhs        <- c(15, 7, 3, 5, 1)
model$sense      <- c('=', '<=', '<=', '<=', '>')
model$vtype      <- 'I'
params <- list(OutputFlag = 1, Presolve = 2, TimeLimit = 3600)
result <- gurobi::gurobi(model, params)

names(result)
[1] "status" "runtime" "itercount" "baritercount" "nodecount" "objval" "x" "slack" "objbound"

Answer 1

感谢 Greg Glockner 的回答 I found something in the documentation，我将其复制到这里。

Gurobi 8.0.0 版本似乎有很多改进！

# Copyright 2018, Gurobi Optimization, LLC
#
# This example reads an LP model from a file and solves it.
# If the model can be solved, then it finds the smallest positive variable,
# sets its upper bound to zero, and resultolves the model two ways:
# first with an advanced start, then without an advanced start
# (i.e. 'from scratch').

library(Matrix)
library(gurobi)

args <- commandArgs(trailingOnly = TRUE)
if (length(args) < 1) {
  stop('Usage: Rscript lpmod.R filename\n')
}

# Read model
cat('Reading model',args[1],'...')
model <- gurobi_read(args[1])
cat('... done\n')

# Determine whether it is an LP
if ('multiobj'  %in% names(model) ||
    'sos'       %in% names(model) ||
    'pwlobj'    %in% names(model) ||
    'cones'     %in% names(model) ||
    'quadcon'   %in% names(model) ||
    'genconstr' %in% names(model)   ) {
  stop('The model is not a linear program\n')
}

# Detect set of non-continuous variables
intvars    <- which(model$vtype != 'C')
numintvars <- length(intvars)
if (numintvars > 0) {
  stop('problem is a MIP, nothing to do\n')
}

# Optimize
result <- gurobi(model)
if (result$status != 'OPTIMAL') {
  cat('This model cannot be solved because its optimization status is',
      result$status, '\n')
  stop('Stop now\n')
}

# Recover number of variables in model
numvars   <- ncol(model$A)

# Ensure bounds array is initialized
if (is.null(model$lb)) {
  model$lb <- rep(0, numvars)
}
if (is.null(model$ub)) {
  model$ub <- rep(Inf, numvars)
}

# Find smallest (non-zero) variable value with zero lower bound
x      <- replace(result$x, result$x < 1e-4, Inf)
x      <- replace(x, model$lb > 1e-6, Inf)
minVar <- which.min(x)
minVal <- x[minVar]

# Get variable name
varname <- ''
if (is.null(model$varnames)) {
  varname <- sprintf('C%d',minVar)
} else {
  varname <- model$varnames[minVar]
}

cat('\n*** Setting', varname, 'from', minVal, 'to zero ***\n\n')
model$ub[minVar] <- 0

# Set advance start basis information
model$vbasis <- result$vbasis
model$cbasis <- result$cbasis

result2   <- gurobi(model)
warmCount <- result2$itercount
warmTime  <- result2$runtime

# Reset-advance start information
model$vbasis <- NULL
model$cbasis <- NULL

result2   <- gurobi(model)
coldCount <- result2$itercount
coldTime  <- result2$runtime

cat('\n*** Warm start:', warmCount, 'iterations,', warmTime, 'seconds\n')
cat('\n*** Cold start:', coldCount, 'iterations,', coldTime, 'seconds\n')

# Clear space
rm(model, result, result2)

如何将 Gurobi 的 vbasis 和 cbasis 与 R-Interface 一起使用？

How can you use Gurobi's vbasis and cbasis with the R-Interface?

r

gurobi