add_lsymphony_solver: Add a SYMPHONY solver with lpsymphony

Description

Specify that the SYMPHONY software should be used to solve a conservation planning problem using the lpsymphony package. This function can also be used to customize the behavior of the solver. It requires the lpsymphony package.

Usage

add_lpsymphony_solver(x, gap = 0.1, time_limit = -1,
  first_feasible = 0, verbose = TRUE)

Arguments

ConservationProblem-class object.

gap

numeric gap to optimality. This gap is absolute and expresses the acceptable deviance from the optimal objective. For example, solving a minimum set objective problem with a gap of 5 will cause the solver to terminate when the cost of the solution is within 5 cost units from the optimal solution.

time_limit

numeric time limit in seconds to run the optimizer. The solver will return the current best solution when this time limit is exceeded.

first_feasible

logical should the first feasible solution be be returned? If first_feasible is set to TRUE, the solver will return the first solution it encounters that meets all the constraints, regardless of solution quality. Note that the first feasible solution is not an arbitrary solution, rather it is derived from the relaxed solution, and is therefore often reasonably close to optimality.

verbose

logical should information be printed while solving optimization problems? Defaults to TRUE.

Value

ConservationProblem-class object with the solver added to it.

Details

SYMPHONY is an open-source integer programming solver that is part of the Computational Infrastructure for Operations Research (COIN-OR) project, an initiative to promote development of open-source tools for operations research (a field that includes linear programming). The lpsymphony package is distributed through Bioconductor. This functionality is provided because the lpsymphony package may be easier to install to install on Windows and Mac OSX systems than the Rsymphony package.

Examples

Run this code

# NOT RUN {
# load data
data(sim_pu_raster, sim_features)

# create problem
p <- problem(sim_pu_raster, sim_features) %>%
  add_min_set_objective() %>%
  add_relative_targets(0.1) %>%
  add_binary_decisions()
# }
# NOT RUN {
# if the package is installed then add solver and generate solution
# note that this solver is skipped on Linux systems due to the fact
# that the lpsymphony package randomly crashes on these systems
if (require(lpsymphony) &
    isTRUE(Sys.info()[["sysname"]] != "Linux")) {
  # specify solver and generate solution
  s <- p %>% add_lpsymphony_solver(time_limit = 5) %>%
             solve()

  # plot solutions
  plot(stack(sim_pu_raster, s), main = c("planning units", "solution"))
}
# }
# NOT RUN {
# }